[midend-IVE]参考libdivide库，实现了魔数的正确求解，如果后续出错直接用API或者不要除法强度削弱了

Pass_ID_List.md

@@ -228,6 +228,173 @@ Branch 和 Return 指令: 这些是终结符指令，不产生一个可用于其
 
 在提供的代码中，SSAPValue 的 constantVal 是 int 类型。这使得浮点数常量传播变得复杂。对于浮点数相关的指令（kFAdd, kFMul, kFCmp, kFNeg, kFNot, kItoF, kFtoI 等），如果不能将浮点值准确地存储在 int 中，或者不能可靠地执行浮点运算，那么通常会保守地将结果设置为 Bottom。一个更完善的 SCCP 实现会使用 std::variant<int, float> 或独立的浮点常量存储来处理浮点数。
 
+## LoopSR循环归纳变量强度削弱 关于魔数计算的说明
+
+魔数除法的核心思想是：将除法转换为乘法和移位
+
+数学原理：x / d ≈ (x * m) >> (32 + s)
+
+m 是魔数 (magic number)
+s 是额外的移位量 (shift)
+>> 是算术右移
+
+2^(32+s) / d ≤ m < 2^(32+s) / d + 2^s / d
+
+cd /home/downright/Compiler_Opt/mysysy && python3 -c "
+# 真正的迭代原因：精度要求
+def explain_precision_requirement():
+    d = 10
+    
+    print('魔数算法需要找到精确的边界值：')
+    print('目标：2^p > d * (2^31 - r)，其中r是余数')
+    print()
+    
+    # 模拟我们算法的迭代过程
+    p = 31
+    two_p = 2**p
+    r = two_p % d  # 余数
+    m = two_p // d  # 商
+    
+    print(f'初始状态 (p={p}):')
+    print(f'  2^{p} = {two_p:,}')
+    print(f'  2^{p} / {d} = {m:,} 余 {r}')
+    print(f'  需要检查: 2^{p} > {d} * (2^31 - {r}) = {d * (2**31 - r):,}')
+    print(f'  条件满足: {two_p > d * (2**31 - r)}')
+    print()
+    
+    # 继续迭代直到条件满足
+    iteration = 0
+    while r != 0 and m < 2**31:
+        iteration += 1
+        p += 1
+        two_p *= 2
+        m *= 2
+        r *= 2
+        if r >= d:
+            m += 1
+            r -= d
+            
+        print(f'迭代 {iteration} (p={p}):')
+        print(f'  m = {m:,}, r = {r}')
+        print(f'  m < 2^31? {m < 2**31} (2^31 = {2**31:,})')
+        
+        if m >= 2**31:
+            print(f'  ✗ 魔数 {m:,} 超出32位范围!')
+            break
+        elif r == 0:
+            print(f'  ✓ 余数为0，找到精确解')
+            break
+        
+        if iteration > 10:  # 防止无限循环
+            print('  ... (限制迭代次数)')
+            break
+
+explain_precision_requirement()
+"
+
+问题在于精度要求。理论魔数需要非常精确，不能简单地用 2^32 / d。让我展示真正的迭代原因：
+
+cd /home/downright/Compiler_Opt/mysysy && python3 -c "
+# 真正的迭代原因：精度要求
+def explain_precision_requirement():
+    d = 10
+    
+    print('魔数算法需要找到精确的边界值：')
+    print('目标：2^p > d * (2^31 - r)，其中r是余数')
+    print()
+    
+    # 模拟我们算法的迭代过程
+    p = 31
+    two_p = 2**p
+    r = two_p % d  # 余数
+    m = two_p // d  # 商
+    
+    print(f'初始状态 (p={p}):')
+    print(f'  2^{p} = {two_p:,}')
+    print(f'  2^{p} / {d} = {m:,} 余 {r}')
+    print(f'  需要检查: 2^{p} > {d} * (2^31 - {r}) = {d * (2**31 - r):,}')
+    print(f'  条件满足: {two_p > d * (2**31 - r)}')
+    print()
+    
+    # 继续迭代直到条件满足
+    iteration = 0
+    while r != 0 and m < 2**31:
+        iteration += 1
+        p += 1
+        two_p *= 2
+        m *= 2
+        r *= 2
+        if r >= d:
+            m += 1
+            r -= d
+            
+        print(f'迭代 {iteration} (p={p}):')
+        print(f'  m = {m:,}, r = {r}')
+        print(f'  m < 2^31? {m < 2**31} (2^31 = {2**31:,})')
+        
+        if m >= 2**31:
+            print(f'  ✗ 魔数 {m:,} 超出32位范围!')
+            break
+        elif r == 0:
+            print(f'  ✓ 余数为0，找到精确解')
+            break
+        
+        if iteration > 10:  # 防止无限循环
+            print('  ... (限制迭代次数)')
+            break
+
+explain_precision_requirement()
+"
+
+
+cd /home/downright/Compiler_Opt/mysysy && python3 -c "
+# 检查初始状态是否会溢出
+def check_initial_overflow():
+    int32_max = 2**31 - 1
+    
+    print('检查不同除数的初始魔数是否会溢出:')
+    print(f'32位有符号整数最大值: {int32_max:,}')
+    print()
+    
+    # 检查各种除数
+    divisors = [2, 3, 5, 7, 9, 10, 11, 13, 17, 25, 100, 1000]
+    
+    for d in divisors:
+        # 初始魔数 = 2^31 / d
+        initial_magic = (2**31) // d
+        
+        overflow = initial_magic > int32_max
+        status = \"溢出\" if overflow else \"安全\"
+        
+        print(f'd={d:4d}: 初始魔数 = 2^31/{d} = {initial_magic:10,} [{status}]')
+        
+    print()
+    print('结论: 初始状态下魔数不会溢出，溢出发生在迭代过程中')
+
+check_initial_overflow()
+"
+
+总结
+迭代的必要性：
+
+不是为了避免初始溢出（初始状态安全）
+是为了找到最精确的魔数，减少舍入误差
+每次迭代提高一倍精度，但魔数也翻倍
+溢出发生时机：
+
+初始状态：2^31 / d 总是在32位范围内
+迭代过程：2^32 / d, 2^33 / d, ... 逐渐超出32位范围
+回退值的正确性：
+
+回退值是基于数学理论和实践验证的标准值
+来自LLVM、GCC等成熟编译器的实现
+通过测试验证，对各种输入都能产生正确结果
+算法设计哲学：
+
+先尝试最优解：通过迭代寻找最精确的魔数
+检测边界条件：当超出32位范围时及时发现
+智能回退：使用已验证的标准值保证正确性
+保持通用性：对于没有预设值的除数仍然可以工作
 
 # 后续优化可能涉及的改动
 

src/backend/RISCv64/RISCv64ISel.cpp

@@ -517,7 +517,7 @@ void RISCv64ISel::selectNode(DAGNode* node) {
                     CurMBB->addInstruction(std::move(instr));
                     break;
                 }
-                case Instruction::kSRA: {
+                case Instruction::kSra: {
                     auto rhs_const = dynamic_cast<ConstantInteger*>(rhs);
                     auto instr = std::make_unique<MachineInstr>(RVOpcodes::SRAIW);
                     instr->addOperand(std::make_unique<RegOperand>(dest_vreg));

src/include/midend/IR.h

@@ -727,6 +727,7 @@ class Instruction : public User {
     kFCmpGE = 0x1UL << 20,
     kAnd = 0x1UL << 21,
     kOr = 0x1UL << 22,
+    // kXor = 0x1UL << 46,
     // Unary
     kNeg = 0x1UL << 23,
     kNot = 0x1UL << 24,
@@ -751,8 +752,10 @@ class Instruction : public User {
     kPhi = 0x1UL << 39,
     kBitItoF = 0x1UL << 40,
     kBitFtoI = 0x1UL << 41,
-    kSRA = 0x1UL << 42,
-    kMulh = 0x1UL << 43
+    kSrl = 0x1UL << 42, // 逻辑右移
+    kSll = 0x1UL << 43, // 逻辑左移
+    kSra = 0x1UL << 44, // 算术右移
+    kMulh = 0x1UL << 45
   };
 
 protected:
@@ -855,8 +858,14 @@ public:
         return "BitItoF";
       case kBitFtoI:
         return "BitFtoI";
-      case kSRA:
+      case kSrl:
+        return "lshr";
+      case kSll:
+        return "shl";
+      case kSra:
         return "ashr";
+      case kMulh:
+        return "mulh";
       default:
         return "Unknown";
     }
@@ -868,7 +877,7 @@ public:
 
   bool isBinary() const {
     static constexpr uint64_t BinaryOpMask =
-        (kAdd | kSub | kMul | kDiv | kRem | kAnd | kOr | kSRA | kMulh) |
+        (kAdd | kSub | kMul | kDiv | kRem | kAnd | kOr | kSra | kSrl | kSll | kMulh) |
         (kICmpEQ | kICmpNE | kICmpLT | kICmpGT | kICmpLE | kICmpGE);
     return kind & BinaryOpMask;
   }
@@ -962,7 +971,13 @@ class PhiInst : public Instruction {
 
   Value* getValfromBlk(BasicBlock* block);
   BasicBlock* getBlkfromVal(Value* value);
-
+  auto getIncomingValues() const {
+    std::vector<std::pair<BasicBlock*, Value*>> result;
+    for (const auto& [block, value] : blk2val) {
+      result.emplace_back(block, value);
+    }
+    return result;
+  }
   void addIncoming(Value *value, BasicBlock *block) {
     assert(value && block && "PhiInst: value and block cannot be null");
     addOperand(value);
@@ -1420,8 +1435,19 @@ protected:
     auto is_same_ptr = [blockToRemove](const std::unique_ptr<BasicBlock> &ptr) { return ptr.get() == blockToRemove; };
     blocks.remove_if(is_same_ptr);
   }
+  BasicBlock* addBasicBlock(const std::string &name, BasicBlock *before) {
+    // 在指定的基本块之前添加一个新的基本块
+    auto it = std::find_if(blocks.begin(), blocks.end(),
+                           [before](const std::unique_ptr<BasicBlock> &ptr) { return ptr.get() == before; });
+    if (it != blocks.end()) {
+      auto newblk = blocks.emplace(it, std::make_unique<BasicBlock>(this, name));
+      return newblk->get();  // 返回新添加的基本块指针
+    }
+    assert(false && "BasicBlock to insert before not found!"); 
+    return nullptr;  // 如果没有找到指定的基本块，则返回nullptr
+  }  ///< 添加一个新的基本块到某个基本块之前
   BasicBlock* addBasicBlock(const std::string &name = "") {
-    blocks.emplace_back(new BasicBlock(this, name));
+    blocks.emplace_back(std::make_unique<BasicBlock>(this, name));
     return blocks.back().get();
   }
   BasicBlock* addBasicBlock(BasicBlock *block) {

src/include/midend/IRBuilder.h

@@ -217,8 +217,14 @@ class IRBuilder {
   BinaryInst * createOrInst(Value *lhs, Value *rhs, const std::string &name = "") {
     return createBinaryInst(Instruction::kOr, Type::getIntType(), lhs, rhs, name);
   }  ///< 创建按位或指令
-  BinaryInst * createSRAInst(Value *lhs, Value *rhs, const std::string &name = "") {
-    return createBinaryInst(Instruction::kSRA, Type::getIntType(), lhs, rhs, name);
+  BinaryInst * createSllInst(Value *lhs, Value *rhs, const std::string &name = "") {
+    return createBinaryInst(Instruction::kSll, Type::getIntType(), lhs, rhs, name);
+  }  ///< 创建逻辑左移指令
+  BinaryInst * createSrlInst(Value *lhs, Value *rhs, const std::string &name = "") {
+    return createBinaryInst(Instruction::kSrl, Type::getIntType(), lhs, rhs, name);
+  }  ///< 创建逻辑右移指令
+  BinaryInst * createSraInst(Value *lhs, Value *rhs, const std::string &name = "") {
+    return createBinaryInst(Instruction::kSra, Type::getIntType(), lhs, rhs, name);
   }  ///< 创建算术右移指令
   BinaryInst * createMulhInst(Value *lhs, Value *rhs, const std::string &name = "") {
     return createBinaryInst(Instruction::kMulh, Type::getIntType(), lhs, rhs, name);

src/include/midend/Pass/Analysis/AliasAnalysis.h

@@ -0,0 +1,246 @@
+#pragma once
+
+#include "IR.h"
+#include "Pass.h"
+#include <map>
+#include <set>
+#include <vector>
+#include <memory>
+
+namespace sysy {
+
+// 前向声明
+class MemoryLocation;
+class AliasAnalysisResult;
+
+/**
+ * @brief 别名关系类型
+ * 按风险等级递增排序
+ */
+enum class AliasType {
+  NO_ALIAS = 0,        // 确定无别名 (不同的局部数组)
+  SELF_ALIAS = 1,      // 自别名 (同一数组的不同索引)
+  POSSIBLE_ALIAS = 2,  // 可能有别名 (函数参数数组)
+  UNKNOWN_ALIAS = 3    // 未知 (保守估计)
+};
+
+/**
+ * @brief 内存位置信息
+ * 描述一个内存访问的基础信息
+ */
+struct MemoryLocation {
+  Value* basePointer;              // 基指针 (剥离GEP后的真实基址)
+  Value* accessPointer;            // 访问指针 (包含索引信息)
+  
+  // 分类信息
+  bool isLocalArray;               // 是否为局部数组
+  bool isFunctionParameter;        // 是否为函数参数
+  bool isGlobalArray;              // 是否为全局数组
+  
+  // 索引信息
+  std::vector<Value*> indices;     // GEP索引列表
+  bool hasConstantIndices;         // 是否为常量索引
+  bool hasLoopVariableIndex;       // 是否包含循环变量
+  int constantOffset;              // 常量偏移量 (仅当全部为常量时有效)
+  
+  // 访问模式
+  bool hasReads;                   // 是否有读操作
+  bool hasWrites;                  // 是否有写操作
+  std::vector<Instruction*> accessInsts; // 所有访问指令
+  
+  MemoryLocation(Value* base, Value* access) 
+    : basePointer(base), accessPointer(access), 
+      isLocalArray(false), isFunctionParameter(false), isGlobalArray(false),
+      hasConstantIndices(false), hasLoopVariableIndex(false), constantOffset(0),
+      hasReads(false), hasWrites(false) {}
+};
+
+/**
+ * @brief 别名分析结果
+ * 存储一个函数的完整别名分析信息
+ */
+class AliasAnalysisResult : public AnalysisResultBase {
+public:
+  AliasAnalysisResult(Function *F) : AssociatedFunction(F) {}
+  ~AliasAnalysisResult() override = default;
+
+  // ========== 基础查询接口 ==========
+  
+  /**
+   * 查询两个指针之间的别名关系
+   */
+  AliasType queryAlias(Value* ptr1, Value* ptr2) const;
+  
+  /**
+   * 查询指针的内存位置信息
+   */
+  const MemoryLocation* getMemoryLocation(Value* ptr) const;
+  
+  /**
+   * 获取所有内存位置
+   */
+  const std::map<Value*, std::unique_ptr<MemoryLocation>>& getAllMemoryLocations() const {
+    return LocationMap;
+  }
+  
+  // ========== 高级查询接口 ==========
+  
+  /**
+   * 检查指针是否为局部数组
+   */
+  bool isLocalArray(Value* ptr) const;
+  
+  /**
+   * 检查指针是否为函数参数数组
+   */
+  bool isFunctionParameter(Value* ptr) const;
+  
+  /**
+   * 检查指针是否为全局数组
+   */
+  bool isGlobalArray(Value* ptr) const;
+  
+  /**
+   * 检查指针是否使用常量索引
+   */
+  bool hasConstantAccess(Value* ptr) const;
+  
+  // ========== 统计接口 ==========
+  
+  /**
+   * 获取各类别名类型的统计信息
+   */
+  struct Statistics {
+    int totalQueries;
+    int noAlias;
+    int selfAlias;
+    int possibleAlias;
+    int unknownAlias;
+    int localArrays;
+    int functionParameters;
+    int globalArrays;
+    int constantAccesses;
+  };
+  
+  Statistics getStatistics() const;
+  
+  /**
+   * 打印别名分析结果 (调试用)
+   */
+  void print() const;
+  void printStatics() const;
+  // ========== 内部方法 ==========
+  
+  void addMemoryLocation(std::unique_ptr<MemoryLocation> location);
+  void addAliasRelation(Value* ptr1, Value* ptr2, AliasType type);
+  
+  // ========== 公开数据成员 (供Pass使用) ==========
+  std::map<Value*, std::unique_ptr<MemoryLocation>> LocationMap;  // 内存位置映射
+  std::map<std::pair<Value*, Value*>, AliasType> AliasMap;        // 别名关系缓存
+
+private:
+  Function *AssociatedFunction;                                    // 关联的函数
+  
+  // 分类存储
+  std::vector<Argument*> ArrayParameters;                         // 数组参数
+  std::vector<AllocaInst*> LocalArrays;                          // 局部数组
+  std::set<GlobalValue*> AccessedGlobals;                        // 访问的全局变量
+};
+
+/**
+ * @brief SysY语言特化的别名分析Pass
+ * 针对SysY语言特性优化的别名分析实现
+ */
+class SysYAliasAnalysisPass : public AnalysisPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+  // 在这里开启激进分析策略
+  SysYAliasAnalysisPass() : AnalysisPass("SysYAliasAnalysis", Pass::Granularity::Function), 
+                           aggressiveParameterMode(false), parameterOptimizationEnabled(false) {}
+
+  // 实现 getPassID
+  void *getPassID() const override { return &ID; }
+
+  // 核心运行方法
+  bool runOnFunction(Function *F, AnalysisManager &AM) override;
+
+  // 获取分析结果
+  std::unique_ptr<AnalysisResultBase> getResult() override { return std::move(CurrentResult); }
+  
+  // ========== 配置接口 ==========
+  
+  /**
+   * 启用针对SysY评测的激进优化模式
+   * 在这种模式下，假设不同参数不会传入相同数组
+   */
+  void enableSysYTestingMode() {
+    aggressiveParameterMode = true;
+    parameterOptimizationEnabled = true;
+  }
+  
+  /**
+   * 使用保守的默认模式（适合通用场景）
+   */
+  void useConservativeMode() {
+    aggressiveParameterMode = false;
+    parameterOptimizationEnabled = false;
+  }
+
+private:
+  std::unique_ptr<AliasAnalysisResult> CurrentResult; // 当前函数的分析结果
+  
+  // ========== 主要分析流程 ==========
+  
+  void collectMemoryAccesses(Function* F);              // 收集内存访问
+  void buildAliasRelations(Function* F);                // 构建别名关系
+  void optimizeForSysY(Function* F);                    // SysY特化优化
+  
+  // ========== 内存位置分析 ==========
+  
+  std::unique_ptr<MemoryLocation> createMemoryLocation(Value* ptr);
+  Value* getBasePointer(Value* ptr);                    // 获取基指针
+  void analyzeMemoryType(MemoryLocation* location);     // 分析内存类型
+  void analyzeIndexPattern(MemoryLocation* location);   // 分析索引模式
+  
+  // ========== 别名关系推断 ==========
+  
+  AliasType analyzeAliasBetween(MemoryLocation* loc1, MemoryLocation* loc2);
+  AliasType compareIndices(MemoryLocation* loc1, MemoryLocation* loc2);
+  AliasType compareLocalArrays(MemoryLocation* loc1, MemoryLocation* loc2);
+  AliasType compareParameters(MemoryLocation* loc1, MemoryLocation* loc2);
+  AliasType compareWithGlobal(MemoryLocation* loc1, MemoryLocation* loc2);
+  AliasType compareMixedTypes(MemoryLocation* loc1, MemoryLocation* loc2);
+  
+  // ========== SysY特化优化 ==========
+  
+  void applySysYConstraints(Function* F);               // 应用SysY语言约束
+  void optimizeParameterAnalysis(Function* F);          // 优化参数分析
+  void optimizeArrayAccessAnalysis(Function* F);        // 优化数组访问分析
+  
+  // ========== 配置和策略控制 ==========
+  
+  bool useAggressiveParameterAnalysis() const { return aggressiveParameterMode; }
+  bool enableParameterOptimization() const { return parameterOptimizationEnabled; }
+  void setAggressiveParameterMode(bool enable) { aggressiveParameterMode = enable; }
+  void setParameterOptimizationEnabled(bool enable) { parameterOptimizationEnabled = enable; }
+  
+  // ========== 辅助优化方法 ==========
+  
+  void optimizeConstantIndexAccesses();                 // 优化常量索引访问
+  void optimizeSequentialAccesses();                   // 优化顺序访问
+  
+  // ========== 辅助方法 ==========
+  
+  bool isConstantValue(Value* val);                     // 是否为常量
+  bool hasLoopVariableInIndices(const std::vector<Value*>& indices, Function* F);
+  int calculateConstantOffset(const std::vector<Value*>& indices);
+  void printStatistics() const;                         // 打印统计信息
+
+private:
+  // ========== 配置选项 ==========
+  bool aggressiveParameterMode = false;                // 激进的参数别名分析模式
+  bool parameterOptimizationEnabled = false;           // 启用参数优化
+};
+
+} // namespace sysy

src/include/midend/Pass/Analysis/CallGraphAnalysis.h

@@ -0,0 +1,242 @@
+#pragma once
+
+#include "IR.h"
+#include "Pass.h"
+#include <map>
+#include <set>
+#include <vector>
+#include <memory>
+#include <algorithm>
+#include <unordered_set>
+
+namespace sysy {
+
+// 前向声明
+class CallGraphAnalysisResult;
+
+/**
+ * @brief 调用图节点信息
+ * 存储单个函数在调用图中的信息
+ */
+struct CallGraphNode {
+    Function* function;                    // 关联的函数
+    std::set<Function*> callers;           // 调用此函数的函数集合
+    std::set<Function*> callees;           // 此函数调用的函数集合
+    
+    // 递归信息
+    bool isRecursive;                      // 是否参与递归调用
+    bool isSelfRecursive;                  // 是否自递归
+    int recursiveDepth;                    // 递归深度(-1表示无限递归)
+    
+    // 调用统计
+    size_t totalCallers;                   // 调用者总数
+    size_t totalCallees;                   // 被调用函数总数
+    size_t callSiteCount;                  // 调用点总数
+    
+    CallGraphNode(Function* f) : function(f), isRecursive(false), 
+        isSelfRecursive(false), recursiveDepth(0), totalCallers(0), 
+        totalCallees(0), callSiteCount(0) {}
+};
+
+/**
+ * @brief 调用图分析结果类
+ * 包含整个模块的调用图信息和查询接口
+ */
+class CallGraphAnalysisResult : public AnalysisResultBase {
+public:
+    CallGraphAnalysisResult(Module* M) : AssociatedModule(M) {}
+    ~CallGraphAnalysisResult() override = default;
+
+    // ========== 基础查询接口 ==========
+    
+    /**
+     * 获取函数的调用图节点
+     */
+    const CallGraphNode* getNode(Function* F) const {
+        auto it = nodes.find(F);
+        return (it != nodes.end()) ? it->second.get() : nullptr;
+    }
+    
+    /**
+     * 获取函数的调用图节点（非const版本）
+     */
+    CallGraphNode* getMutableNode(Function* F) {
+        auto it = nodes.find(F);
+        return (it != nodes.end()) ? it->second.get() : nullptr;
+    }
+    
+    /**
+     * 获取所有函数节点
+     */
+    const std::map<Function*, std::unique_ptr<CallGraphNode>>& getAllNodes() const {
+        return nodes;
+    }
+    
+    /**
+     * 检查函数是否存在于调用图中
+     */
+    bool hasFunction(Function* F) const {
+        return nodes.find(F) != nodes.end();
+    }
+
+    // ========== 调用关系查询 ==========
+    
+    /**
+     * 检查是否存在从caller到callee的调用
+     */
+    bool hasCallEdge(Function* caller, Function* callee) const {
+        auto node = getNode(caller);
+        return node && node->callees.count(callee) > 0;
+    }
+    
+    /**
+     * 获取函数的所有调用者
+     */
+    std::vector<Function*> getCallers(Function* F) const {
+        auto node = getNode(F);
+        if (!node) return {};
+        return std::vector<Function*>(node->callers.begin(), node->callers.end());
+    }
+    
+    /**
+     * 获取函数的所有被调用函数
+     */
+    std::vector<Function*> getCallees(Function* F) const {
+        auto node = getNode(F);
+        if (!node) return {};
+        return std::vector<Function*>(node->callees.begin(), node->callees.end());
+    }
+
+    // ========== 递归分析查询 ==========
+    
+    /**
+     * 检查函数是否参与递归调用
+     */
+    bool isRecursive(Function* F) const {
+        auto node = getNode(F);
+        return node && node->isRecursive;
+    }
+    
+    /**
+     * 检查函数是否自递归
+     */
+    bool isSelfRecursive(Function* F) const {
+        auto node = getNode(F);
+        return node && node->isSelfRecursive;
+    }
+    
+    /**
+     * 获取递归深度
+     */
+    int getRecursiveDepth(Function* F) const {
+        auto node = getNode(F);
+        return node ? node->recursiveDepth : 0;
+    }
+
+    // ========== 拓扑排序和SCC ==========
+    
+    /**
+     * 获取函数的拓扑排序结果
+     * 保证被调用函数在调用函数之前
+     */
+    const std::vector<Function*>& getTopologicalOrder() const {
+        return topologicalOrder;
+    }
+    
+    /**
+     * 获取强连通分量列表
+     * 每个SCC表示一个递归函数群
+     */
+    const std::vector<std::vector<Function*>>& getStronglyConnectedComponents() const {
+        return sccs;
+    }
+    
+    /**
+     * 获取函数所在的SCC索引
+     */
+    int getSCCIndex(Function* F) const {
+        auto it = functionToSCC.find(F);
+        return (it != functionToSCC.end()) ? it->second : -1;
+    }
+
+    // ========== 统计信息 ==========
+    
+    struct Statistics {
+        size_t totalFunctions;
+        size_t totalCallEdges;
+        size_t recursiveFunctions;
+        size_t selfRecursiveFunctions;
+        size_t stronglyConnectedComponents;
+        size_t maxSCCSize;
+        double avgCallersPerFunction;
+        double avgCalleesPerFunction;
+    };
+    
+    Statistics getStatistics() const;
+    
+    /**
+     * 打印调用图分析结果
+     */
+    void print() const;
+
+    // ========== 内部构建接口 ==========
+    
+    void addNode(Function* F);
+    void addCallEdge(Function* caller, Function* callee);
+    void computeTopologicalOrder();
+    void computeStronglyConnectedComponents();
+    void analyzeRecursion();
+
+private:
+    Module* AssociatedModule;                                      // 关联的模块
+    std::map<Function*, std::unique_ptr<CallGraphNode>> nodes;     // 调用图节点
+    std::vector<Function*> topologicalOrder;                      // 拓扑排序结果
+    std::vector<std::vector<Function*>> sccs;                     // 强连通分量
+    std::map<Function*, int> functionToSCC;                       // 函数到SCC的映射
+    
+    // 内部辅助方法
+    void dfsTopological(Function* F, std::unordered_set<Function*>& visited, 
+                       std::vector<Function*>& result);
+    void tarjanSCC();
+    void tarjanDFS(Function* F, int& index, std::vector<int>& indices, 
+                  std::vector<int>& lowlinks, std::vector<Function*>& stack, 
+                  std::unordered_set<Function*>& onStack);
+};
+
+/**
+ * @brief SysY调用图分析Pass
+ * Module级别的分析Pass，构建整个模块的函数调用图
+ */
+class CallGraphAnalysisPass : public AnalysisPass {
+public:
+    // 唯一的 Pass ID
+    static void* ID;
+
+    CallGraphAnalysisPass() : AnalysisPass("CallGraphAnalysis", Pass::Granularity::Module) {}
+
+    // 实现 getPassID
+    void* getPassID() const override { return &ID; }
+
+    // 核心运行方法
+    bool runOnModule(Module* M, AnalysisManager& AM) override;
+
+    // 获取分析结果
+    std::unique_ptr<AnalysisResultBase> getResult() override { return std::move(CurrentResult); }
+
+private:
+    std::unique_ptr<CallGraphAnalysisResult> CurrentResult;  // 当前模块的分析结果
+    
+    // ========== 主要分析流程 ==========
+    
+    void buildCallGraph(Module* M);                          // 构建调用图
+    void scanFunctionCalls(Function* F);                     // 扫描函数的调用
+    void processCallInstruction(CallInst* call, Function* caller);  // 处理调用指令
+    
+    // ========== 辅助方法 ==========
+    
+    bool isLibraryFunction(Function* F) const;               // 判断是否为标准库函数
+    bool isIntrinsicFunction(Function* F) const;             // 判断是否为内置函数
+    void printStatistics() const;                            // 打印统计信息
+};
+
+} // namespace sysy

src/include/midend/Pass/Analysis/Loop.h

@@ -0,0 +1,618 @@
+#pragma once
+
+#include "Dom.h"
+#include "IR.h"
+#include "Pass.h"
+#include <algorithm>
+#include <functional>
+#include <map>
+#include <memory>
+#include <optional>
+#include <queue>
+#include <set>
+#include <vector>
+
+namespace sysy {
+
+// 前向声明
+class LoopAnalysisResult;
+class AliasAnalysisResult;
+class SideEffectAnalysisResult;
+
+/**
+ * @brief 表示一个识别出的循环。
+ */
+class Loop {
+private:
+  static int NextLoopID; // 静态变量用于分配唯一ID
+  int LoopID;
+public:
+  // 构造函数：指定循环头
+  Loop(BasicBlock *header) : Header(header), LoopID(NextLoopID++) {}
+
+  // 获取循环头
+  BasicBlock *getHeader() const { return Header; }
+
+  // 获取循环的名称 （基于ID）
+  std::string getName() const { return "loop_" + std::to_string(LoopID); }
+  // 获取循环体包含的所有基本块
+  const std::set<BasicBlock *> &getBlocks() const { return LoopBlocks; }
+
+  // 获取循环的出口基本块（即从循环内部跳转到循环外部的基本块）
+  const std::set<BasicBlock *> &getExitBlocks() const { return ExitBlocks; }
+
+  // 获取循环前置块（如果存在），可以为 nullptr
+  BasicBlock *getPreHeader() const { return PreHeader; }
+
+  // 获取直接包含此循环的父循环（如果存在），可以为 nullptr
+  Loop *getParentLoop() const { return ParentLoop; }
+
+  // 获取直接嵌套在此循环内的子循环
+  const std::vector<Loop *> &getNestedLoops() const { return NestedLoops; }
+
+  // 获取循环的层级 (0 表示最外层循环，1 表示嵌套一层，以此类推)
+  int getLoopLevel() const { return Level; }
+
+  // 检查一个基本块是否属于当前循环
+  bool contains(BasicBlock *BB) const { return LoopBlocks.count(BB); }
+
+  // 判断当前循环是否是最内层循环 (没有嵌套子循环)
+  bool isInnermost() const { return NestedLoops.empty(); }
+
+  // 获取循环的深度（从最外层开始计算）
+  int getLoopDepth() const { return Level + 1; }
+
+  // 获取循环体的大小（基本块数量）
+  size_t getLoopSize() const { return LoopBlocks.size(); }
+
+  // 检查循环是否有唯一的外部前驱（即是否有前置块）
+  bool hasUniquePreHeader() const { return PreHeader != nullptr; }
+
+  // 检查循环是否是最外层循环（没有父循环）
+  bool isOutermost() const { return getParentLoop() == nullptr; }
+
+  // 获取循环的所有出口（从循环内到循环外的基本块）
+  std::vector<BasicBlock*> getExitingBlocks() const {
+    std::vector<BasicBlock*> exitingBlocks;
+    for (BasicBlock* bb : LoopBlocks) {
+      for (BasicBlock* succ : bb->getSuccessors()) {
+        if (!contains(succ)) {
+          exitingBlocks.push_back(bb);
+          break; // 每个基本块只添加一次
+        }
+      }
+    }
+    return exitingBlocks;
+  }
+
+  // 判断循环是否是简单循环（只有一个回边）
+  bool isSimpleLoop() const {
+    int backEdgeCount = 0;
+    for (BasicBlock* pred : Header->getPredecessors()) {
+      if (contains(pred)) {
+        backEdgeCount++;
+      }
+    }
+    return backEdgeCount == 1;
+  }
+
+  /**
+   * 获取所有出口目标块 (循环外接收循环出口边的块)
+   * 使用场景: 循环后置处理、phi节点分析
+   */
+  std::vector<BasicBlock*> getExitTargetBlocks() const {
+    std::set<BasicBlock*> exitTargetSet;
+    for (BasicBlock* bb : LoopBlocks) {
+      for (BasicBlock* succ : bb->getSuccessors()) {
+        if (!contains(succ)) {
+          exitTargetSet.insert(succ);
+        }
+      }
+    }
+    return std::vector<BasicBlock*>(exitTargetSet.begin(), exitTargetSet.end());
+  }
+
+  /**
+   * 计算循环的"深度"相对于指定的祖先循环
+   * 使用场景: 相对深度计算、嵌套分析
+   */
+  int getRelativeDepth(Loop* ancestor) const {
+    if (this == ancestor) return 0;
+    
+    int depth = 0;
+    Loop* current = this->ParentLoop;
+    while (current && current != ancestor) {
+      depth++;
+      current = current->ParentLoop;
+    }
+    
+    return current == ancestor ? depth : -1; // -1表示不是祖先关系
+  }
+
+  /**
+   * 检查循环是否包含函数调用
+   * 使用场景: 内联决策、副作用分析
+   */
+  bool containsFunctionCalls() const {
+    for (BasicBlock* bb : LoopBlocks) {
+      for (auto& inst : bb->getInstructions()) {
+        if (dynamic_cast<CallInst*>(inst.get())) {
+          return true;
+        }
+      }
+    }
+    return false;
+  }
+
+  /**
+   * 检查循环是否可能有副作用（基于副作用分析结果）
+   * 使用场景: 循环优化决策、并行化分析
+   */
+  bool mayHaveSideEffects(SideEffectAnalysisResult* sideEffectAnalysis) const;
+
+  /**
+   * 检查循环是否访问全局内存（基于别名分析结果）
+   * 使用场景: 并行化分析、缓存优化
+   */
+  bool accessesGlobalMemory(AliasAnalysisResult* aliasAnalysis) const;
+
+  /**
+   * 检查循环是否有可能的内存别名冲突
+   * 使用场景: 向量化分析、并行化决策
+   */
+  bool hasMemoryAliasConflicts(AliasAnalysisResult* aliasAnalysis) const;
+
+  /**
+   * 估算循环的"热度" (基于嵌套深度和大小)
+   * 使用场景: 优化优先级、资源分配
+   */
+  double getLoopHotness() const {
+    // 简单的热度估算: 深度权重 + 大小惩罚
+    double hotness = std::pow(2.0, Level); // 深度越深越热
+    hotness /= std::sqrt(LoopBlocks.size()); // 大小越大相对热度降低
+    return hotness;
+  }
+
+  // --- 供 LoopAnalysisPass 内部调用的方法，用于构建 Loop 对象 ---
+  void addBlock(BasicBlock *BB) { LoopBlocks.insert(BB); }
+  void addExitBlock(BasicBlock *BB) { ExitBlocks.insert(BB); }
+  void setPreHeader(BasicBlock *BB) { PreHeader = BB; }
+  void setParentLoop(Loop *loop) { ParentLoop = loop; }
+  void addNestedLoop(Loop *loop) { NestedLoops.push_back(loop); }
+  void setLoopLevel(int level) { Level = level; }
+  void clearNestedLoops() { NestedLoops.clear(); }
+private:
+  BasicBlock *Header;                // 循环头基本块
+  std::set<BasicBlock *> LoopBlocks; // 循环体包含的基本块集合
+  std::set<BasicBlock *> ExitBlocks; // 循环出口基本块集合
+  BasicBlock *PreHeader = nullptr;   // 循环前置块 (Optional)
+  Loop *ParentLoop = nullptr;        // 父循环 (用于嵌套)
+  std::vector<Loop *> NestedLoops;   // 嵌套的子循环
+  int Level = -1;                    // 循环的层级，-1表示未计算
+};
+
+/**
+ * @brief 循环分析结果类。
+ * 包含一个函数中所有识别出的循环，并提供高效的查询缓存机制。
+ */
+class LoopAnalysisResult : public AnalysisResultBase {
+public:
+  LoopAnalysisResult(Function *F) : AssociatedFunction(F) {}
+  ~LoopAnalysisResult() override = default;
+
+  // ========== 缓存统计结构 ==========
+  struct CacheStats {
+    size_t innermostLoopsCached;
+    size_t outermostLoopsCached;
+    size_t loopsByDepthCached;
+    size_t containingLoopsCached;
+    size_t allNestedLoopsCached;
+    size_t totalCachedQueries;
+  };
+
+private:
+  // ========== 高频查询缓存 ==========
+  mutable std::optional<std::vector<Loop*>> cachedInnermostLoops;
+  mutable std::optional<std::vector<Loop*>> cachedOutermostLoops;
+  mutable std::optional<int> cachedMaxDepth;
+  mutable std::optional<size_t> cachedLoopCount;
+  mutable std::map<int, std::vector<Loop*>> cachedLoopsByDepth;
+  
+  // ========== 中频查询缓存 ==========
+  mutable std::map<BasicBlock*, Loop*> cachedInnermostContainingLoop;
+  mutable std::map<Loop*, std::set<Loop*>> cachedAllNestedLoops; // 递归嵌套
+  mutable std::map<BasicBlock*, std::vector<Loop*>> cachedAllContainingLoops;
+  
+  // ========== 缓存状态管理 ==========
+  mutable bool cacheValid = true;
+
+  // 内部辅助方法
+  void invalidateCache() const {
+    cachedInnermostLoops.reset();
+    cachedOutermostLoops.reset();
+    cachedMaxDepth.reset();
+    cachedLoopCount.reset();
+    cachedLoopsByDepth.clear();
+    cachedInnermostContainingLoop.clear();
+    cachedAllNestedLoops.clear();
+    cachedAllContainingLoops.clear();
+    cacheValid = false;
+  }
+  
+  void ensureCacheValid() const {
+    if (!cacheValid) {
+      // 重新计算基础缓存
+      computeBasicCache();
+      cacheValid = true;
+    }
+  }
+  
+  void computeBasicCache() const {
+    // 计算最内层循环
+    if (!cachedInnermostLoops) {
+      cachedInnermostLoops = std::vector<Loop*>();
+      for (const auto& loop : AllLoops) {
+        if (loop->isInnermost()) {
+          cachedInnermostLoops->push_back(loop.get());
+        }
+      }
+    }
+    
+    // 计算最外层循环
+    if (!cachedOutermostLoops) {
+      cachedOutermostLoops = std::vector<Loop*>();
+      for (const auto& loop : AllLoops) {
+        if (loop->isOutermost()) {
+          cachedOutermostLoops->push_back(loop.get());
+        }
+      }
+    }
+    
+    // 计算最大深度
+    if (!cachedMaxDepth) {
+      int maxDepth = 0;
+      for (const auto& loop : AllLoops) {
+        maxDepth = std::max(maxDepth, loop->getLoopDepth());
+      }
+      cachedMaxDepth = maxDepth;
+    }
+    
+    // 计算循环总数
+    if (!cachedLoopCount) {
+      cachedLoopCount = AllLoops.size();
+    }
+  }
+
+public:
+  // ========== 基础接口 ==========
+
+  // 添加一个识别出的循环到结果中
+  void addLoop(std::unique_ptr<Loop> loop) {
+    invalidateCache(); // 添加新循环时失效缓存
+    AllLoops.push_back(std::move(loop));
+    LoopMap[AllLoops.back()->getHeader()] = AllLoops.back().get();
+  }
+
+  // 获取所有识别出的循环（unique_ptr 管理内存）
+  const std::vector<std::unique_ptr<Loop>> &getAllLoops() const { return AllLoops; }
+
+  // ========== 高频查询接口 ==========
+  
+  /**
+   * 获取所有最内层循环 - 循环优化的主要目标
+   * 使用场景: 循环展开、向量化、循环不变量外提
+   */
+  const std::vector<Loop*>& getInnermostLoops() const {
+    ensureCacheValid();
+    if (!cachedInnermostLoops) {
+      cachedInnermostLoops = std::vector<Loop*>();
+      for (const auto& loop : AllLoops) {
+        if (loop->isInnermost()) {
+          cachedInnermostLoops->push_back(loop.get());
+        }
+      }
+    }
+    return *cachedInnermostLoops;
+  }
+  
+  /**
+   * 获取所有最外层循环
+   * 使用场景: 循环树遍历、整体优化策略
+   */
+  const std::vector<Loop*>& getOutermostLoops() const {
+    ensureCacheValid();
+    if (!cachedOutermostLoops) {
+      cachedOutermostLoops = std::vector<Loop*>();
+      for (const auto& loop : AllLoops) {
+        if (loop->isOutermost()) {
+          cachedOutermostLoops->push_back(loop.get());
+        }
+      }
+    }
+    return *cachedOutermostLoops;
+  }
+  
+  /**
+   * 获取指定深度的所有循环
+   * 使用场景: 分层优化、循环展开决策、并行化分析
+   */
+  const std::vector<Loop*>& getLoopsAtDepth(int depth) const {
+    ensureCacheValid();
+    if (cachedLoopsByDepth.find(depth) == cachedLoopsByDepth.end()) {
+      std::vector<Loop*> result;
+      for (const auto& loop : AllLoops) {
+        if (loop->getLoopDepth() == depth) {
+          result.push_back(loop.get());
+        }
+      }
+      cachedLoopsByDepth[depth] = std::move(result);
+    }
+    return cachedLoopsByDepth[depth];
+  }
+  
+  /**
+   * 获取最大循环嵌套深度
+   * 使用场景: 优化预算分配、编译时间控制
+   */
+  int getMaxLoopDepth() const {
+    ensureCacheValid();
+    if (!cachedMaxDepth) {
+      int maxDepth = 0;
+      for (const auto& loop : AllLoops) {
+        maxDepth = std::max(maxDepth, loop->getLoopDepth());
+      }
+      cachedMaxDepth = maxDepth;
+    }
+    return *cachedMaxDepth;
+  }
+  
+  /**
+   * 获取循环总数
+   * 使用场景: 统计信息、优化决策
+   */
+  size_t getLoopCount() const {
+    ensureCacheValid();
+    if (!cachedLoopCount) {
+      cachedLoopCount = AllLoops.size();
+    }
+    return *cachedLoopCount;
+  }
+
+  // 获取指定深度的循环数量
+  size_t getLoopCountAtDepth(int depth) const {
+    return getLoopsAtDepth(depth).size();
+  }
+
+  // 检查函数是否包含循环
+  bool hasLoops() const { return !AllLoops.empty(); }
+
+  // ========== 中频查询接口 ==========
+  
+  /**
+   * 获取包含指定基本块的最内层循环
+   * 使用场景: 活跃性分析、寄存器分配、指令调度
+   */
+  Loop* getInnermostContainingLoop(BasicBlock* BB) const {
+    ensureCacheValid();
+    if (cachedInnermostContainingLoop.find(BB) == cachedInnermostContainingLoop.end()) {
+      Loop* result = nullptr;
+      int maxDepth = -1;
+      for (const auto& loop : AllLoops) {
+        if (loop->contains(BB) && loop->getLoopDepth() > maxDepth) {
+          result = loop.get();
+          maxDepth = loop->getLoopDepth();
+        }
+      }
+      cachedInnermostContainingLoop[BB] = result;
+    }
+    return cachedInnermostContainingLoop[BB];
+  }
+  
+  /**
+   * 获取包含指定基本块的所有循环 (从外到内排序)
+   * 使用场景: 循环间优化、依赖分析
+   */
+  const std::vector<Loop*>& getAllContainingLoops(BasicBlock* BB) const {
+    ensureCacheValid();
+    if (cachedAllContainingLoops.find(BB) == cachedAllContainingLoops.end()) {
+      std::vector<Loop*> result;
+      for (const auto& loop : AllLoops) {
+        if (loop->contains(BB)) {
+          result.push_back(loop.get());
+        }
+      }
+      // 按深度排序 (外层到内层)
+      std::sort(result.begin(), result.end(), 
+                [](Loop* a, Loop* b) { return a->getLoopDepth() < b->getLoopDepth(); });
+      cachedAllContainingLoops[BB] = std::move(result);
+    }
+    return cachedAllContainingLoops[BB];
+  }
+  
+  /**
+   * 获取指定循环的所有嵌套子循环 (递归)
+   * 使用场景: 循环树分析、嵌套优化
+   */
+  const std::set<Loop*>& getAllNestedLoops(Loop* loop) const {
+    ensureCacheValid();
+    if (cachedAllNestedLoops.find(loop) == cachedAllNestedLoops.end()) {
+      std::set<Loop*> result;
+      std::function<void(Loop*)> collectNested = [&](Loop* current) {
+        for (Loop* nested : current->getNestedLoops()) {
+          result.insert(nested);
+          collectNested(nested); // 递归收集
+        }
+      };
+      collectNested(loop);
+      cachedAllNestedLoops[loop] = std::move(result);
+    }
+    return cachedAllNestedLoops[loop];
+  }
+
+  // ========== 利用别名和副作用分析的查询接口 ==========
+  
+  /**
+   * 获取所有纯循环（无副作用的循环）
+   * 并行化、循环优化
+   */
+  std::vector<Loop*> getPureLoops(SideEffectAnalysisResult* sideEffectAnalysis) const {
+    std::vector<Loop*> result;
+    if (!sideEffectAnalysis) return result;
+    
+    for (const auto& loop : AllLoops) {
+      if (!loop->mayHaveSideEffects(sideEffectAnalysis)) {
+        result.push_back(loop.get());
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 获取所有只访问局部内存的循环
+   * 缓存优化、局部性分析
+   */
+  std::vector<Loop*> getLocalMemoryLoops(AliasAnalysisResult* aliasAnalysis) const {
+    std::vector<Loop*> result;
+    if (!aliasAnalysis) return result;
+    
+    for (const auto& loop : AllLoops) {
+      if (!loop->accessesGlobalMemory(aliasAnalysis)) {
+        result.push_back(loop.get());
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 获取所有无内存别名冲突的循环
+   * 向量化、并行化
+   */
+  std::vector<Loop*> getNoAliasConflictLoops(AliasAnalysisResult* aliasAnalysis) const {
+    std::vector<Loop*> result;
+    if (!aliasAnalysis) return result;
+    
+    for (const auto& loop : AllLoops) {
+      if (!loop->hasMemoryAliasConflicts(aliasAnalysis)) {
+        result.push_back(loop.get());
+      }
+    }
+    return result;
+  }
+
+  // ========== 低频查询接口(不缓存) ==========
+  
+  /**
+   * 检查两个循环是否有嵌套关系
+   * 循环间依赖分析
+   */
+  bool isNestedLoop(Loop* inner, Loop* outer) const {
+    if (inner == outer) return false;
+    
+    Loop* current = inner->getParentLoop();
+    while (current) {
+      if (current == outer) return true;
+      current = current->getParentLoop();
+    }
+    return false;
+  }
+  
+  /**
+   * 获取两个循环的最近公共祖先循环
+   * 循环融合分析、优化范围确定
+   */
+  Loop* getLowestCommonAncestor(Loop* loop1, Loop* loop2) const {
+    if (!loop1 || !loop2) return nullptr;
+    if (loop1 == loop2) return loop1;
+    
+    // 收集loop1的所有祖先
+    std::set<Loop*> ancestors1;
+    Loop* current = loop1;
+    while (current) {
+      ancestors1.insert(current);
+      current = current->getParentLoop();
+    }
+    
+    // 查找loop2祖先链中第一个在ancestors1中的循环
+    current = loop2;
+    while (current) {
+      if (ancestors1.count(current)) {
+        return current;
+      }
+      current = current->getParentLoop();
+    }
+    
+    return nullptr; // 没有公共祖先
+  }
+
+  // 通过循环头获取 Loop 对象
+  Loop *getLoopForHeader(BasicBlock *header) const {
+    auto it = LoopMap.find(header);
+    return (it != LoopMap.end()) ? it->second : nullptr;
+  }
+
+  // 通过某个基本块获取包含它的最内层循环 (向后兼容接口)
+  Loop *getLoopContainingBlock(BasicBlock *BB) const {
+    return getInnermostContainingLoop(BB);
+  }
+
+  // ========== 缓存管理接口 ==========
+  
+  /**
+   * 手动失效缓存 (可删除)
+   */
+  void invalidateQueryCache() const {
+    invalidateCache();
+  }
+  
+  /**
+   * 获取缓存统计信息
+   */
+  CacheStats getCacheStats() const {
+    CacheStats stats = {};
+    stats.innermostLoopsCached = cachedInnermostLoops.has_value() ? 1 : 0;
+    stats.outermostLoopsCached = cachedOutermostLoops.has_value() ? 1 : 0;
+    stats.loopsByDepthCached = cachedLoopsByDepth.size();
+    stats.containingLoopsCached = cachedInnermostContainingLoop.size();
+    stats.allNestedLoopsCached = cachedAllNestedLoops.size();
+    stats.totalCachedQueries = stats.innermostLoopsCached + stats.outermostLoopsCached + 
+                               stats.loopsByDepthCached + stats.containingLoopsCached + 
+                               stats.allNestedLoopsCached;
+    return stats;
+  }
+
+  // 打印分析结果
+  void print() const;
+  void printBBSet(const std::string &prefix, const std::set<BasicBlock *> &s) const;
+  void printLoopVector(const std::string &prefix, const std::vector<Loop *> &loops) const;
+
+private:
+  Function *AssociatedFunction;                // 结果关联的函数
+  std::vector<std::unique_ptr<Loop>> AllLoops; // 所有识别出的循环
+  std::map<BasicBlock *, Loop *> LoopMap;      // 循环头到 Loop* 的映射，方便查找
+};
+
+/**
+ * @brief 循环分析遍。
+ * 识别函数中的所有循环，并生成 LoopAnalysisResult。
+ */
+class LoopAnalysisPass : public AnalysisPass {
+public:
+  // 唯一的 Pass ID，需要在 .cpp 文件中定义
+  static void *ID;
+
+  LoopAnalysisPass() : AnalysisPass("LoopAnalysis", Pass::Granularity::Function) {}
+
+  // 实现 getPassID
+  void *getPassID() const override { return &ID; }
+
+  // 核心运行方法：在每个函数上执行循环分析
+  bool runOnFunction(Function *F, AnalysisManager &AM) override;
+
+  // 获取分析结果
+  std::unique_ptr<AnalysisResultBase> getResult() override { return std::move(CurrentResult); }
+
+private:
+  std::unique_ptr<LoopAnalysisResult> CurrentResult; // 当前函数的分析结果
+};
+
+} // namespace sysy

src/include/midend/Pass/Analysis/LoopCharacteristics.h

@@ -0,0 +1,356 @@
+#pragma once
+
+#include "Dom.h"         // 支配树分析依赖
+#include "Loop.h"        // 循环分析依赖
+#include "Liveness.h"    // 活跃性分析依赖
+#include "AliasAnalysis.h" // 别名分析依赖
+#include "SideEffectAnalysis.h" // 副作用分析依赖
+#include "CallGraphAnalysis.h" // 调用图分析依赖
+#include "IR.h"          // IR定义
+#include "Pass.h"        // Pass框架
+#include <algorithm>
+#include <map>
+#include <memory>
+#include <optional>
+#include <set>
+#include <vector>
+
+namespace sysy {
+
+// 前向声明
+class LoopCharacteristicsResult;
+
+enum IVKind {
+  kBasic,        // 基本归纳变量
+  kLinear,     // 线性归纳变量
+  kCmplx       // 复杂派生归纳变量
+} ;          // 归纳变量类型
+
+struct InductionVarInfo {
+  Value* div;                  // 派生归纳变量的指令
+  Value* base = nullptr;                 // 其根phi或BIV或DIV
+  std::pair<Value*, Value*> Multibase = {nullptr, nullptr}; // 多个BIV
+  Instruction::Kind Instkind;      // 操作类型
+  int factor = 1;              // 系数（如i*2+3的2）
+  int offset = 0;              // 常量偏移
+  bool valid;    // 是否线性可归约
+  IVKind ivkind;          // 归纳变量类型
+
+
+static std::unique_ptr<InductionVarInfo> createBasicBIV(Value* v, Instruction::Kind kind, Value* base = nullptr, int factor = 1, int offset = 0) {
+  return std::make_unique<InductionVarInfo>(
+    InductionVarInfo{v, base, {nullptr, nullptr}, kind, factor, offset, true, IVKind::kBasic}
+  );
+}
+
+static std::unique_ptr<InductionVarInfo> createSingleDIV(Value* v, Instruction::Kind kind, Value* base = nullptr, int factor = 1, int offset = 0) {
+  return std::make_unique<InductionVarInfo>(
+    InductionVarInfo{v, base, {nullptr, nullptr}, kind, factor, offset, true,  IVKind::kLinear}
+  );
+}
+
+static std::unique_ptr<InductionVarInfo> createDoubleDIV(Value* v, Instruction::Kind kind, Value* base1 = nullptr,  Value* base2 = nullptr, int factor = 1, int offset = 0) {
+  return std::make_unique<InductionVarInfo>(
+    InductionVarInfo{v, nullptr, {base1, base2}, kind, factor, offset, false, IVKind::kCmplx}
+  );
+}
+};
+
+/**
+ * @brief 循环特征信息结构 - 基础循环分析阶段
+ * 存储循环的基本特征信息，为后续精确分析提供基础
+ */
+struct LoopCharacteristics {
+  Loop* loop;                                    // 关联的循环对象
+
+  // ========== 基础循环形式分析 ==========
+  bool isCountingLoop;                         // 是否为计数循环 (for i=0; i<n; i++)
+  bool isSimpleForLoop;                        // 是否为简单for循环
+  bool hasComplexControlFlow;                  // 是否有复杂控制流 (break, continue)
+  bool isInnermost;                            // 是否为最内层循环
+  
+  // ========== 归纳变量分析 ==========
+  
+  // ========== 基础循环不变量分析 ==========
+  std::unordered_set<Value*> loopInvariants;              // 循环不变量
+  std::unordered_set<Instruction*> invariantInsts;       // 可提升的不变指令
+
+  std::vector<std::unique_ptr<InductionVarInfo>> InductionVars;     // 归纳变量
+  
+  // ========== 基础边界分析 ==========
+  std::optional<int> staticTripCount;          // 静态循环次数（如果可确定）
+  bool hasKnownBounds;                         // 是否有已知边界
+  
+  // ========== 基础纯度和副作用分析 ==========
+  bool isPure;                                 // 是否为纯循环（无副作用）
+  bool accessesOnlyLocalMemory;                // 是否只访问局部内存
+  bool hasNoMemoryAliasConflicts;              // 是否无内存别名冲突
+  
+  // ========== 基础内存访问模式分析 ==========
+  struct MemoryAccessPattern {
+    std::vector<Instruction*> loadInsts;       // load指令列表
+    std::vector<Instruction*> storeInsts;      // store指令列表
+    bool isArrayParameter;                     // 是否为数组参数访问
+    bool isGlobalArray;                        // 是否为全局数组访问
+    bool hasConstantIndices;                   // 是否使用常量索引
+  };
+  std::map<Value*, MemoryAccessPattern> memoryPatterns; // 内存访问模式
+  
+  // ========== 基础性能特征 ==========
+  size_t instructionCount;                     // 循环体指令数
+  size_t memoryOperationCount;                 // 内存操作数
+  size_t arithmeticOperationCount;             // 算术操作数
+  double computeToMemoryRatio;                 // 计算与内存操作比率
+  
+  // ========== 基础优化提示 ==========
+  bool benefitsFromUnrolling;                  // 是否适合循环展开
+  int suggestedUnrollFactor;                   // 建议的展开因子
+  
+  // 构造函数 - 简化的基础分析初始化
+  LoopCharacteristics(Loop* l) : loop(l), 
+    isCountingLoop(false), isSimpleForLoop(false), hasComplexControlFlow(false),
+    isInnermost(false), hasKnownBounds(false), isPure(false), 
+    accessesOnlyLocalMemory(false), hasNoMemoryAliasConflicts(false),
+    benefitsFromUnrolling(false), suggestedUnrollFactor(1), 
+    instructionCount(0), memoryOperationCount(0),
+    arithmeticOperationCount(0), computeToMemoryRatio(0.0) {}
+};
+
+/**
+ * @brief 循环特征分析结果类
+ * 包含函数中所有循环的特征信息，并提供查询接口
+ */
+class LoopCharacteristicsResult : public AnalysisResultBase {
+public:
+  LoopCharacteristicsResult(Function *F) : AssociatedFunction(F) {}
+  ~LoopCharacteristicsResult() override = default;
+
+  // ========== 基础接口 ==========
+  
+  /**
+   * 添加循环特征信息
+   */
+  void addLoopCharacteristics(std::unique_ptr<LoopCharacteristics> characteristics) {
+    auto* loop = characteristics->loop;
+    CharacteristicsMap[loop] = std::move(characteristics);
+  }
+  
+  /**
+   * 获取指定循环的特征信息
+   */
+  const LoopCharacteristics* getCharacteristics(Loop* loop) const {
+    auto it = CharacteristicsMap.find(loop);
+    return (it != CharacteristicsMap.end()) ? it->second.get() : nullptr;
+  }
+  
+  /**
+   * 获取所有循环特征信息
+   */
+  const std::map<Loop*, std::unique_ptr<LoopCharacteristics>>& getAllCharacteristics() const {
+    return CharacteristicsMap;
+  }
+
+  // ========== 核心查询接口 ==========
+  
+  /**
+   * 获取所有计数循环
+   */
+  std::vector<Loop*> getCountingLoops() const {
+    std::vector<Loop*> result;
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      if (chars->isCountingLoop) {
+        result.push_back(loop);
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 获取所有纯循环（无副作用）
+   */
+  std::vector<Loop*> getPureLoops() const {
+    std::vector<Loop*> result;
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      if (chars->isPure) {
+        result.push_back(loop);
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 获取所有只访问局部内存的循环
+   */
+  std::vector<Loop*> getLocalMemoryOnlyLoops() const {
+    std::vector<Loop*> result;
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      if (chars->accessesOnlyLocalMemory) {
+        result.push_back(loop);
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 获取所有无内存别名冲突的循环
+   */
+  std::vector<Loop*> getNoAliasConflictLoops() const {
+    std::vector<Loop*> result;
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      if (chars->hasNoMemoryAliasConflicts) {
+        result.push_back(loop);
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 获取所有适合展开的循环
+   */
+  std::vector<Loop*> getUnrollingCandidates() const {
+    std::vector<Loop*> result;
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      if (chars->benefitsFromUnrolling) {
+        result.push_back(loop);
+      }
+    }
+    return result;
+  }
+  
+  /**
+   * 根据热度排序循环 (用于优化优先级)
+   */
+  std::vector<Loop*> getLoopsByHotness() const {
+    std::vector<Loop*> result;
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      result.push_back(loop);
+    }
+    
+    // 按循环热度排序 (嵌套深度 + 循环次数 + 指令数)
+    std::sort(result.begin(), result.end(), [](Loop* a, Loop* b) {
+      double hotnessA = a->getLoopHotness();
+      double hotnessB = b->getLoopHotness();
+      return hotnessA > hotnessB; // 降序排列
+    });
+    
+    return result;
+  }
+
+  // ========== 基础统计接口 ==========
+  
+  /**
+   * 获取基础优化统计信息
+   */
+  struct BasicOptimizationStats {
+    size_t totalLoops;
+    size_t countingLoops;
+    size_t unrollingCandidates;
+    size_t pureLoops;
+    size_t localMemoryOnlyLoops;
+    size_t noAliasConflictLoops;
+    double avgInstructionCount;
+    double avgComputeMemoryRatio;
+  };
+  
+  BasicOptimizationStats getOptimizationStats() const {
+    BasicOptimizationStats stats = {};
+    stats.totalLoops = CharacteristicsMap.size();
+    
+    size_t totalInstructions = 0;
+    double totalComputeMemoryRatio = 0.0;
+    
+    for (const auto& [loop, chars] : CharacteristicsMap) {
+      if (chars->isCountingLoop) stats.countingLoops++;
+      if (chars->benefitsFromUnrolling) stats.unrollingCandidates++;
+      if (chars->isPure) stats.pureLoops++;
+      if (chars->accessesOnlyLocalMemory) stats.localMemoryOnlyLoops++;
+      if (chars->hasNoMemoryAliasConflicts) stats.noAliasConflictLoops++;
+      
+      totalInstructions += chars->instructionCount;
+      totalComputeMemoryRatio += chars->computeToMemoryRatio;
+    }
+    
+    if (stats.totalLoops > 0) {
+      stats.avgInstructionCount = static_cast<double>(totalInstructions) / stats.totalLoops;
+      stats.avgComputeMemoryRatio = totalComputeMemoryRatio / stats.totalLoops;
+    }
+    
+    return stats;
+  }
+
+  // 打印分析结果
+  void print() const;
+
+private:
+  Function *AssociatedFunction;                                    // 关联的函数
+  std::map<Loop*, std::unique_ptr<LoopCharacteristics>> CharacteristicsMap; // 循环特征映射
+};
+
+/**
+ * @brief 基础循环特征分析遍
+ * 在循环规范化前执行，进行基础的循环特征分析，为后续精确分析提供基础
+ */
+class LoopCharacteristicsPass : public AnalysisPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+
+  LoopCharacteristicsPass() : AnalysisPass("LoopCharacteristics", Pass::Granularity::Function) {}
+
+  // 实现 getPassID
+  void *getPassID() const override { return &ID; }
+
+  // 核心运行方法
+  bool runOnFunction(Function *F, AnalysisManager &AM) override;
+
+  // 获取分析结果
+  std::unique_ptr<AnalysisResultBase> getResult() override { return std::move(CurrentResult); }
+
+private:
+  std::unique_ptr<LoopCharacteristicsResult> CurrentResult;
+  
+  // ========== 缓存的分析结果 ==========
+  LoopAnalysisResult* loopAnalysis;           // 循环结构分析结果
+  AliasAnalysisResult* aliasAnalysis;         // 别名分析结果  
+  SideEffectAnalysisResult* sideEffectAnalysis; // 副作用分析结果
+  
+  // ========== 核心分析方法 ==========
+  void analyzeLoop(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础循环形式分析
+  void analyzeLoopForm(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础性能指标计算
+  void computePerformanceMetrics(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础纯度和副作用分析
+  void analyzePurityAndSideEffects(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础归纳变量识别
+  void identifyBasicInductionVariables(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 循环不变量识别
+  void identifyBasicLoopInvariants(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础边界分析
+  void analyzeBasicLoopBounds(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础内存访问模式分析
+  void analyzeBasicMemoryAccessPatterns(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // 基础优化评估
+  void evaluateBasicOptimizationOpportunities(Loop* loop, LoopCharacteristics* characteristics);
+  
+  // ========== 辅助方法 ==========
+  bool isClassicLoopInvariant(Value* val, Loop* loop, const std::unordered_set<Value*>& invariants);
+  void findDerivedInductionVars(Value* root,
+    Value* base, // 只传单一BIV base
+    Loop* loop,
+    std::vector<std::unique_ptr<InductionVarInfo>>& ivs,
+    std::set<Value*>& visited
+  );
+  bool isBasicInductionVariable(Value* val, Loop* loop);
+  bool hasSimpleMemoryPattern(Loop* loop); // 简单的内存模式检查
+};
+
+} // namespace sysy

src/include/midend/Pass/Analysis/LoopVectorization.h

@@ -0,0 +1,250 @@
+#pragma once
+
+#include "Pass.h"
+#include "Loop.h" 
+#include "LoopCharacteristics.h"
+#include "AliasAnalysis.h"
+#include "SideEffectAnalysis.h"
+#include <vector>
+#include <map>
+#include <memory>
+#include <set>
+#include <string>
+
+namespace sysy {
+
+/**
+ * @brief 依赖类型枚举 - 只考虑真正影响并行性的依赖
+ * 
+ * 依赖类型分析说明：
+ * - TRUE_DEPENDENCE (RAW): 真依赖，必须保持原始执行顺序，是最关键的依赖
+ * - ANTI_DEPENDENCE (WAR): 反依赖，影响指令重排序，可通过寄存器重命名等技术缓解
+ * - OUTPUT_DEPENDENCE (WAW): 输出依赖，相对较少但需要考虑，可通过变量私有化解决
+ * 
+ */
+enum class DependenceType {
+  TRUE_DEPENDENCE,    // 真依赖 (RAW) - 读后写流依赖，最重要的依赖类型
+  ANTI_DEPENDENCE,    // 反依赖 (WAR) - 写后读反向依赖，影响指令重排序  
+  OUTPUT_DEPENDENCE   // 输出依赖 (WAW) - 写后写，相对较少但需要考虑
+};
+
+/**
+ * @brief 依赖向量 - 表示两个内存访问之间的迭代距离
+ * 例如：a[i] 和 a[i+1] 之间的依赖向量是 [1]
+ *       a[i][j] 和 a[i+1][j-2] 之间的依赖向量是 [1,-2]
+ */
+struct DependenceVector {
+  std::vector<int> distances;    // 每个循环层次的依赖距离
+  bool isConstant;               // 是否为常量距离
+  bool isKnown;                  // 是否已知距离
+  
+  DependenceVector(size_t loopDepth) : distances(loopDepth, 0), isConstant(false), isKnown(false) {}
+  
+  // 检查是否为循环无关依赖
+  bool isLoopIndependent() const {
+    for (int dist : distances) {
+      if (dist != 0) return false;
+    }
+    return true;
+  }
+  
+  // 获取词典序方向向量
+  std::vector<int> getDirectionVector() const;
+  
+  // 检查是否可以通过向量化处理
+  bool isVectorizationSafe() const;
+};
+
+/**
+ * @brief 精确依赖关系 - 包含依赖向量的详细依赖信息
+ */
+struct PreciseDependence {
+  Instruction* source;
+  Instruction* sink;
+  DependenceType type;
+  DependenceVector dependenceVector;
+  Value* memoryLocation;
+  
+  // 并行化相关
+  bool allowsParallelization;    // 是否允许并行化
+  bool requiresSynchronization;  // 是否需要同步
+  bool isReductionDependence;    // 是否为归约依赖
+  
+  PreciseDependence(size_t loopDepth) : dependenceVector(loopDepth), 
+    allowsParallelization(true), requiresSynchronization(false), isReductionDependence(false) {}
+};
+
+/**
+ * @brief 向量化分析信息 - 暂时搁置，保留接口
+ */
+struct VectorizationAnalysis {
+  bool isVectorizable;                        // 固定为false，暂不支持
+  int suggestedVectorWidth;                   // 固定为1
+  std::vector<std::string> preventingFactors; // 阻止向量化的因素
+  
+  VectorizationAnalysis() : isVectorizable(false), suggestedVectorWidth(1) {
+    preventingFactors.push_back("Vectorization temporarily disabled");
+  }
+};
+
+/**
+ * @brief 并行化分析信息
+ */
+struct ParallelizationAnalysis {
+  bool isParallelizable;                     // 是否可并行化
+  int suggestedThreadCount;                  // 建议的线程数
+  std::vector<std::string> preventingFactors; // 阻止并行化的因素
+  
+  // 并行化模式
+  enum ParallelizationType { 
+    NONE,                    // 不可并行化
+    EMBARRASSINGLY_PARALLEL, // 完全并行
+    REDUCTION_PARALLEL,      // 归约并行
+    PIPELINE_PARALLEL,       // 流水线并行
+    CONDITIONAL_PARALLEL     // 条件并行
+  } parallelType;
+  
+  // 负载均衡
+  bool hasLoadBalance;                       // 是否有良好的负载均衡
+  bool isDynamicLoadBalanced;                // 是否需要动态负载均衡
+  double workComplexity;                     // 工作复杂度估计
+  
+  // 同步需求
+  bool requiresReduction;                    // 是否需要归约操作
+  bool requiresBarrier;                      // 是否需要屏障同步
+  std::set<Value*> sharedVariables;         // 共享变量
+  std::set<Value*> reductionVariables;      // 归约变量
+  std::set<Value*> privatizableVariables;   // 可私有化变量
+  
+  // 内存访问模式
+  bool hasMemoryConflicts;                   // 是否有内存冲突
+  bool hasReadOnlyAccess;                    // 是否只有只读访问
+  bool hasIndependentAccess;                 // 是否有独立的内存访问
+  
+  // 并行化收益评估
+  double parallelizationBenefit;             // 并行化收益估计 (0-1)
+  size_t communicationCost;                  // 通信开销估计
+  size_t synchronizationCost;                // 同步开销估计
+  
+  ParallelizationAnalysis() : isParallelizable(false), suggestedThreadCount(1), parallelType(NONE),
+    hasLoadBalance(true), isDynamicLoadBalanced(false), workComplexity(0.0), requiresReduction(false), 
+    requiresBarrier(false), hasMemoryConflicts(false), hasReadOnlyAccess(false), hasIndependentAccess(false),
+    parallelizationBenefit(0.0), communicationCost(0), synchronizationCost(0) {}
+};
+
+/**
+ * @brief 循环向量化/并行化分析结果
+ */
+class LoopVectorizationResult : public AnalysisResultBase {
+private:
+  Function* AssociatedFunction;
+  std::map<Loop*, VectorizationAnalysis> VectorizationMap;
+  std::map<Loop*, ParallelizationAnalysis> ParallelizationMap;
+  std::map<Loop*, std::vector<PreciseDependence>> DependenceMap;
+
+public:
+  LoopVectorizationResult(Function* F) : AssociatedFunction(F) {}
+  ~LoopVectorizationResult() override = default;
+
+  // 基础接口
+  void addVectorizationAnalysis(Loop* loop, VectorizationAnalysis analysis) {
+    VectorizationMap[loop] = std::move(analysis);
+  }
+  
+  void addParallelizationAnalysis(Loop* loop, ParallelizationAnalysis analysis) {
+    ParallelizationMap[loop] = std::move(analysis);
+  }
+  
+  void addDependenceAnalysis(Loop* loop, std::vector<PreciseDependence> dependences) {
+    DependenceMap[loop] = std::move(dependences);
+  }
+
+  // 查询接口
+  const VectorizationAnalysis* getVectorizationAnalysis(Loop* loop) const {
+    auto it = VectorizationMap.find(loop);
+    return it != VectorizationMap.end() ? &it->second : nullptr;
+  }
+  
+  const ParallelizationAnalysis* getParallelizationAnalysis(Loop* loop) const {
+    auto it = ParallelizationMap.find(loop);
+    return it != ParallelizationMap.end() ? &it->second : nullptr;
+  }
+  
+  const std::vector<PreciseDependence>* getPreciseDependences(Loop* loop) const {
+    auto it = DependenceMap.find(loop);
+    return it != DependenceMap.end() ? &it->second : nullptr;
+  }
+
+  // 统计接口
+  size_t getVectorizableLoopCount() const;
+  size_t getParallelizableLoopCount() const;
+  
+  // 优化建议
+  std::vector<Loop*> getVectorizationCandidates() const;
+  std::vector<Loop*> getParallelizationCandidates() const;
+  
+  // 打印分析结果
+  void print() const;
+};
+
+/**
+ * @brief 循环向量化/并行化分析遍
+ * 在循环规范化后执行，进行精确的依赖向量分析和向量化/并行化可行性评估
+ * 专注于并行化分析，向量化功能暂时搁置
+ */
+class LoopVectorizationPass : public AnalysisPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+  
+  LoopVectorizationPass() : AnalysisPass("LoopVectorization", Pass::Granularity::Function) {}
+
+  // 实现 getPassID
+  void *getPassID() const override { return &ID; }
+
+  // 核心运行方法
+  bool runOnFunction(Function *F, AnalysisManager &AM) override;
+  
+  // 获取分析结果
+  std::unique_ptr<AnalysisResultBase> getResult() override { return std::move(CurrentResult); }
+
+private:
+  std::unique_ptr<LoopVectorizationResult> CurrentResult;
+  
+  // ========== 主要分析方法 ==========
+  void analyzeLoop(Loop* loop, LoopCharacteristics* characteristics, 
+                   AliasAnalysisResult* aliasAnalysis, SideEffectAnalysisResult* sideEffectAnalysis);
+  
+  // ========== 依赖向量分析 ==========
+  std::vector<PreciseDependence> computeDependenceVectors(Loop* loop, AliasAnalysisResult* aliasAnalysis);
+  DependenceVector computeAccessDependence(Instruction* inst1, Instruction* inst2, Loop* loop);
+  bool areAccessesAffinelyRelated(Value* ptr1, Value* ptr2, Loop* loop);
+  
+  // ========== 向量化分析 (暂时搁置) ==========
+  VectorizationAnalysis analyzeVectorizability(Loop* loop, const std::vector<PreciseDependence>& dependences,
+                                              LoopCharacteristics* characteristics);
+  
+  // ========== 并行化分析 ==========
+  ParallelizationAnalysis analyzeParallelizability(Loop* loop, const std::vector<PreciseDependence>& dependences,
+                                                  LoopCharacteristics* characteristics);
+  bool checkParallelizationLegality(Loop* loop, const std::vector<PreciseDependence>& dependences);
+  int estimateOptimalThreadCount(Loop* loop, LoopCharacteristics* characteristics);
+  ParallelizationAnalysis::ParallelizationType determineParallelizationType(Loop* loop, 
+                                                                           const std::vector<PreciseDependence>& dependences);
+  
+  // ========== 并行化专用分析方法 ==========
+  void analyzeReductionPatterns(Loop* loop, ParallelizationAnalysis* analysis);
+  void analyzeMemoryAccessPatterns(Loop* loop, ParallelizationAnalysis* analysis, AliasAnalysisResult* aliasAnalysis);
+  void estimateParallelizationBenefit(Loop* loop, ParallelizationAnalysis* analysis, LoopCharacteristics* characteristics);
+  void identifyPrivatizableVariables(Loop* loop, ParallelizationAnalysis* analysis);
+  void analyzeSynchronizationNeeds(Loop* loop, ParallelizationAnalysis* analysis, const std::vector<PreciseDependence>& dependences);
+  
+  // ========== 辅助方法 ==========
+  std::vector<int> extractInductionCoefficients(Value* ptr, Loop* loop);
+  bool isConstantStride(Value* ptr, Loop* loop, int& stride);
+  bool isIndependentMemoryAccess(Value* ptr1, Value* ptr2, Loop* loop);
+  double estimateWorkComplexity(Loop* loop);
+  bool hasReductionPattern(Value* var, Loop* loop);
+};
+
+} // namespace sysy

src/include/midend/Pass/Analysis/SideEffectAnalysis.h

@@ -0,0 +1,137 @@
+#pragma once
+
+#include "Pass.h"
+#include "IR.h"
+#include "AliasAnalysis.h"
+#include "CallGraphAnalysis.h"
+#include <unordered_set>
+#include <unordered_map>
+
+namespace sysy {
+
+// 副作用类型枚举
+enum class SideEffectType {
+    NO_SIDE_EFFECT,      // 无副作用
+    MEMORY_WRITE,        // 内存写入（store、memset）
+    FUNCTION_CALL,       // 函数调用（可能有任意副作用）
+    IO_OPERATION,        // I/O操作（printf、scanf等）
+    UNKNOWN              // 未知副作用
+};
+
+// 副作用信息结构
+struct SideEffectInfo {
+    SideEffectType type = SideEffectType::NO_SIDE_EFFECT;
+    bool mayModifyGlobal = false;      // 可能修改全局变量
+    bool mayModifyMemory = false;      // 可能修改内存
+    bool mayCallFunction = false;      // 可能调用函数
+    bool isPure = true;                // 是否为纯函数（无副作用且结果只依赖参数）
+    
+    // 合并两个副作用信息
+    SideEffectInfo merge(const SideEffectInfo& other) const {
+        SideEffectInfo result;
+        result.type = (type == SideEffectType::NO_SIDE_EFFECT) ? other.type : type;
+        result.mayModifyGlobal = mayModifyGlobal || other.mayModifyGlobal;
+        result.mayModifyMemory = mayModifyMemory || other.mayModifyMemory;
+        result.mayCallFunction = mayCallFunction || other.mayCallFunction;
+        result.isPure = isPure && other.isPure;
+        return result;
+    }
+};
+
+// 副作用分析结果类
+class SideEffectAnalysisResult : public AnalysisResultBase {
+private:
+    // 指令级别的副作用信息
+    std::unordered_map<Instruction*, SideEffectInfo> instructionSideEffects;
+    
+    // 函数级别的副作用信息
+    std::unordered_map<Function*, SideEffectInfo> functionSideEffects;
+    
+    // 已知的SysY标准库函数副作用信息
+    std::unordered_map<std::string, SideEffectInfo> knownFunctions;
+
+public:
+    SideEffectAnalysisResult();
+    virtual ~SideEffectAnalysisResult() noexcept override = default;
+    
+    // 获取指令的副作用信息
+    const SideEffectInfo& getInstructionSideEffect(Instruction* inst) const;
+    
+    // 获取函数的副作用信息
+    const SideEffectInfo& getFunctionSideEffect(Function* func) const;
+    
+    // 设置指令的副作用信息
+    void setInstructionSideEffect(Instruction* inst, const SideEffectInfo& info);
+    
+    // 设置函数的副作用信息
+    void setFunctionSideEffect(Function* func, const SideEffectInfo& info);
+    
+    // 检查指令是否有副作用
+    bool hasSideEffect(Instruction* inst) const;
+    
+    // 检查指令是否可能修改内存
+    bool mayModifyMemory(Instruction* inst) const;
+    
+    // 检查指令是否可能修改全局状态
+    bool mayModifyGlobal(Instruction* inst) const;
+    
+    // 检查函数是否为纯函数
+    bool isPureFunction(Function* func) const;
+    
+    // 获取已知函数的副作用信息
+    const SideEffectInfo* getKnownFunctionSideEffect(const std::string& funcName) const;
+    
+    // 初始化已知函数的副作用信息
+    void initializeKnownFunctions();
+    
+private:
+};
+
+// 副作用分析遍类 - Module级别分析
+class SysYSideEffectAnalysisPass : public AnalysisPass {
+public:
+    // 静态成员，作为该遍的唯一ID
+    static void* ID;
+    
+    SysYSideEffectAnalysisPass() : AnalysisPass("SysYSideEffectAnalysis", Granularity::Module) {}
+    
+    // 在模块上运行分析
+    bool runOnModule(Module* M, AnalysisManager& AM) override;
+    
+    // 获取分析结果
+    std::unique_ptr<AnalysisResultBase> getResult() override;
+    
+    // Pass 基类中的纯虚函数，必须实现
+    void* getPassID() const override { return &ID; }
+
+private:
+    // 分析结果
+    std::unique_ptr<SideEffectAnalysisResult> result;
+    
+    // 调用图分析结果
+    CallGraphAnalysisResult* callGraphAnalysis = nullptr;
+    
+    // 分析单个函数的副作用（Module级别的内部方法）
+    SideEffectInfo analyzeFunction(Function* func, AnalysisManager& AM);
+    
+    // 分析单个指令的副作用
+    SideEffectInfo analyzeInstruction(Instruction* inst, Function* currentFunc, AnalysisManager& AM);
+    
+    // 分析函数调用指令的副作用（利用调用图）
+    SideEffectInfo analyzeCallInstruction(CallInst* call, Function* currentFunc, AnalysisManager& AM);
+    
+    // 分析存储指令的副作用
+    SideEffectInfo analyzeStoreInstruction(StoreInst* store, Function* currentFunc, AnalysisManager& AM);
+    
+    // 分析内存设置指令的副作用
+    SideEffectInfo analyzeMemsetInstruction(MemsetInst* memset, Function* currentFunc, AnalysisManager& AM);
+    
+    // 使用不动点算法分析递归函数群
+    void analyzeStronglyConnectedComponent(const std::vector<Function*>& scc, AnalysisManager& AM);
+    
+    // 检查函数间副作用传播的收敛性
+    bool hasConverged(const std::unordered_map<Function*, SideEffectInfo>& oldEffects,
+                      const std::unordered_map<Function*, SideEffectInfo>& newEffects) const;
+};
+
+} // namespace sysy

src/include/midend/Pass/Optimize/DCE.h

@@ -4,6 +4,8 @@
 #include "IR.h"
 #include "SysYIROptUtils.h"
 #include "Dom.h" 
+#include "AliasAnalysis.h"
+#include "SideEffectAnalysis.h"
 #include <unordered_set>
 #include <queue>
 
@@ -25,8 +27,12 @@ public:
 private:
     // 存储活跃指令的集合
     std::unordered_set<Instruction*> alive_insts;
+    // 别名分析结果
+    AliasAnalysisResult* aliasAnalysis = nullptr;
+    // 副作用分析结果
+    SideEffectAnalysisResult* sideEffectAnalysis = nullptr;
 
-    // 判断指令是否是“天然活跃”的（即总是保留的）
+    // 判断指令是否是"天然活跃"的（即总是保留的）
     // inst: 要检查的指令
     // 返回值: 如果指令是天然活跃的，则为true，否则为false
     bool isAlive(Instruction* inst);
@@ -34,6 +40,9 @@ private:
     // 递归地将活跃指令及其依赖加入到 alive_insts 集合中
     // inst: 要标记为活跃的指令
     void addAlive(Instruction* inst);
+    
+    // 检查Store指令是否可能有副作用（通过别名分析）
+    bool mayHaveSideEffect(StoreInst* store);
 };
 
 // DCE 优化遍类，继承自 OptimizationPass

src/include/midend/Pass/Optimize/InductionVariableElimination.h

@@ -0,0 +1,157 @@
+#pragma once
+
+#include "Pass.h"
+#include "IR.h"
+#include "LoopCharacteristics.h"
+#include "Loop.h"
+#include "Dom.h"
+#include "SideEffectAnalysis.h"
+#include <vector>
+#include <unordered_map>
+#include <unordered_set>
+#include <memory>
+
+namespace sysy {
+
+// 前向声明
+class LoopCharacteristicsResult;
+class LoopAnalysisResult;
+
+/**
+ * @brief 死归纳变量信息
+ * 记录一个可以被消除的归纳变量
+ */
+struct DeadInductionVariable {
+  PhiInst* phiInst;                    // phi 指令
+  std::vector<Instruction*> relatedInsts; // 相关的递增/递减指令
+  Loop* containingLoop;                // 所在循环
+  bool canEliminate;                   // 是否可以安全消除
+  
+  DeadInductionVariable(PhiInst* phi, Loop* loop) 
+    : phiInst(phi), containingLoop(loop), canEliminate(false) {}
+};
+
+/**
+ * @brief 归纳变量消除上下文类
+ * 封装归纳变量消除优化的核心逻辑和状态
+ */
+class InductionVariableEliminationContext {
+public:
+  InductionVariableEliminationContext() {}
+  
+  /**
+   * 运行归纳变量消除优化
+   * @param F 目标函数
+   * @param AM 分析管理器
+   * @return 是否修改了IR
+   */
+  bool run(Function* F, AnalysisManager& AM);
+
+private:
+  // 分析结果缓存
+  LoopAnalysisResult* loopAnalysis = nullptr;
+  LoopCharacteristicsResult* loopCharacteristics = nullptr;
+  DominatorTree* dominatorTree = nullptr;
+  SideEffectAnalysisResult* sideEffectAnalysis = nullptr;
+  
+  // 死归纳变量存储
+  std::vector<std::unique_ptr<DeadInductionVariable>> deadIVs;
+  std::unordered_map<Loop*, std::vector<DeadInductionVariable*>> loopToDeadIVs;
+  
+  // ========== 核心分析和优化阶段 ==========
+  
+  /**
+   * 阶段1：识别死归纳变量
+   * 找出没有被有效使用的归纳变量
+   */
+  void identifyDeadInductionVariables(Function* F);
+  
+  /**
+   * 阶段2：分析消除的安全性
+   * 确保消除操作不会破坏程序语义
+   */
+  void analyzeSafetyForElimination();
+  
+  /**
+   * 阶段3：执行归纳变量消除
+   * 删除死归纳变量及其相关指令
+   */
+  bool performInductionVariableElimination();
+  
+  // ========== 辅助方法 ==========
+  
+  /**
+   * 检查归纳变量是否为死归纳变量
+   * @param iv 归纳变量信息
+   * @param loop 所在循环
+   * @return 如果是死归纳变量返回相关信息，否则返回nullptr
+   */
+  std::unique_ptr<DeadInductionVariable> 
+  isDeadInductionVariable(const InductionVarInfo* iv, Loop* loop);
+  
+  /**
+   * 检查归纳变量是否只用于自身更新
+   * @param phiInst phi指令
+   * @param loop 所在循环
+   * @return 是否只用于自身更新
+   */
+  bool isUsedOnlyForSelfUpdate(PhiInst* phiInst, Loop* loop);
+  
+  /**
+   * 收集与归纳变量相关的所有指令
+   * @param phiInst phi指令
+   * @param loop 所在循环
+   * @return 相关指令列表
+   */
+  std::vector<Instruction*> collectRelatedInstructions(PhiInst* phiInst, Loop* loop);
+  
+  /**
+   * 检查消除归纳变量的安全性
+   * @param deadIV 死归纳变量
+   * @return 是否可以安全消除
+   */
+  bool isSafeToEliminate(const DeadInductionVariable* deadIV);
+  
+  /**
+   * 消除单个死归纳变量
+   * @param deadIV 死归纳变量
+   * @return 是否成功消除
+   */
+  bool eliminateDeadInductionVariable(DeadInductionVariable* deadIV);
+  
+  /**
+   * 打印调试信息
+   */
+  void printDebugInfo();
+};
+
+/**
+ * @brief 归纳变量消除优化遍
+ * 消除循环中无用的归纳变量，减少寄存器压力
+ */
+class InductionVariableElimination : public OptimizationPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+  
+  InductionVariableElimination() 
+    : OptimizationPass("InductionVariableElimination", Granularity::Function) {}
+  
+  /**
+   * 在函数上运行归纳变量消除优化
+   * @param F 目标函数
+   * @param AM 分析管理器
+   * @return 是否修改了IR
+   */
+  bool runOnFunction(Function* F, AnalysisManager& AM) override;
+  
+  /**
+   * 声明分析依赖和失效信息
+   */
+  void getAnalysisUsage(std::set<void*>& analysisDependencies, 
+                       std::set<void*>& analysisInvalidations) const override;
+  
+  void* getPassID() const override { return &ID; }
+};
+
+} // namespace sysy

src/include/midend/Pass/Optimize/LICM.h

@@ -0,0 +1,40 @@
+#pragma once
+#include "Pass.h"
+#include "Loop.h"
+#include "LoopCharacteristics.h"
+#include "Dom.h"
+#include <unordered_set>
+#include <vector>
+
+namespace sysy{
+
+class LICMContext {
+public:
+  LICMContext(Function* func, Loop* loop, IRBuilder* builder, const LoopCharacteristics* chars)
+    : func(func), loop(loop), builder(builder), chars(chars) {}
+    // 运行LICM主流程，返回IR是否被修改
+    bool run();
+
+private:
+    Function* func;
+    Loop* loop;
+    IRBuilder* builder;
+    const LoopCharacteristics* chars; // 特征分析结果
+
+    // 外提所有可提升指令
+    bool hoistInstructions();
+};
+
+
+class LICM : public OptimizationPass{
+private:
+	IRBuilder *builder; ///< IR构建器，用于插入指令
+public:
+	static void *ID;
+	LICM(IRBuilder *builder = nullptr) : OptimizationPass("LICM", Granularity::Function) , builder(builder) {}
+	bool runOnFunction(Function *F, AnalysisManager &AM) override;
+	void getAnalysisUsage(std::set<void *> &, std::set<void *> &) const override;
+	void *getPassID() const override { return &ID; }
+};
+
+} // namespace sysy

src/include/midend/Pass/Optimize/LoopNormalization.h

@@ -0,0 +1,155 @@
+#pragma once
+
+#include "Loop.h"          // 循环分析依赖
+#include "Dom.h"           // 支配树分析依赖
+#include "IR.h"            // IR定义
+#include "IRBuilder.h"     // IR构建器
+#include "Pass.h"          // Pass框架
+#include <memory>
+#include <set>
+#include <vector>
+
+namespace sysy {
+
+/**
+ * @brief 循环规范化转换Pass
+ * 
+ * 该Pass在循环不变量提升等优化前运行，主要负责：
+ * 1. 为没有前置块(preheader)的循环创建前置块
+ * 2. 确保循环结构符合后续优化的要求
+ * 3. 规范化循环的控制流结构
+ * 
+ * 前置块的作用：
+ * - 为循环不变量提升提供插入位置
+ * - 简化循环分析和优化
+ * - 确保循环有唯一的入口点
+ */
+class LoopNormalizationPass : public OptimizationPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+
+  LoopNormalizationPass(IRBuilder* builder) : OptimizationPass("LoopNormalization", Pass::Granularity::Function), builder(builder) {}
+
+  // 实现 getPassID
+  void *getPassID() const override { return &ID; }
+
+  // 核心运行方法
+  bool runOnFunction(Function *F, AnalysisManager &AM) override;
+  
+  // 声明分析依赖和失效信息
+  void getAnalysisUsage(std::set<void *> &analysisDependencies, std::set<void *> &analysisInvalidations) const override;
+
+private:
+  // ========== IR构建器 ==========
+  IRBuilder* builder;                                  // IR构建器
+  
+  // ========== 缓存的分析结果 ==========
+  LoopAnalysisResult* loopAnalysis;                    // 循环结构分析结果
+  DominatorTree* domTree;                              // 支配树分析结果
+  
+  // ========== 规范化统计 ==========
+  struct NormalizationStats {
+    size_t totalLoops;                    // 总循环数
+    size_t loopsNeedingPreheader;        // 需要前置块的循环数
+    size_t preheadersCreated;            // 创建的前置块数
+    size_t loopsNormalized;              // 规范化的循环数
+    size_t redundantPhisRemoved;         // 删除的冗余PHI节点数
+    
+    NormalizationStats() : totalLoops(0), loopsNeedingPreheader(0), 
+                          preheadersCreated(0), loopsNormalized(0), 
+                          redundantPhisRemoved(0) {}
+  } stats;
+  
+  // ========== 核心规范化方法 ==========
+  
+  /**
+   * 规范化单个循环
+   * @param loop 要规范化的循环
+   * @return 是否进行了修改
+   */
+  bool normalizeLoop(Loop* loop);
+  
+  /**
+   * 为循环创建前置块
+   * @param loop 需要前置块的循环
+   * @return 创建的前置块，如果失败则返回nullptr
+   */
+  BasicBlock* createPreheaderForLoop(Loop* loop);
+  
+  /**
+   * 检查循环是否需要前置块（基于结构性需求）
+   * @param loop 要检查的循环
+   * @return true如果需要前置块
+   */
+  bool needsPreheader(Loop* loop);
+  
+  /**
+   * 检查循环是否已有合适的前置块
+   * @param loop 要检查的循环
+   * @return 现有的前置块，如果没有则返回nullptr
+   */
+  BasicBlock* getExistingPreheader(Loop* loop);
+  
+  /**
+   * 更新支配树关系（在创建新块后）
+   * @param newBlock 新创建的基本块
+   * @param loop 相关的循环
+   */
+  void updateDominatorRelations(BasicBlock* newBlock, Loop* loop);
+  
+  /**
+   * 重定向循环外的前驱块到新的前置块
+   * @param loop 目标循环
+   * @param preheader 新创建的前置块
+   * @param header 循环头部
+   */
+  void redirectExternalPredecessors(Loop* loop, BasicBlock* preheader, BasicBlock* header, const std::vector<BasicBlock*>& externalPreds);
+  
+  /**
+   * 为前置块生成合适的名称
+   * @param loop 相关的循环
+   * @return 生成的前置块名称
+   */
+  std::string generatePreheaderName(Loop* loop);
+  
+  /**
+   * 验证规范化结果的正确性
+   * @param loop 规范化后的循环
+   * @return true如果规范化正确
+   */
+  bool validateNormalization(Loop* loop);
+  
+  // ========== 辅助方法 ==========
+  
+  /**
+   * 获取循环的外部前驱块（不在循环内的前驱）
+   * @param loop 目标循环
+   * @return 外部前驱块列表
+   */
+  std::vector<BasicBlock*> getExternalPredecessors(Loop* loop);
+  
+  /**
+   * 检查基本块是否适合作为前置块
+   * @param block 候选基本块
+   * @param loop 目标循环
+   * @return true如果适合作为前置块
+   */
+  bool isSuitableAsPreheader(BasicBlock* block, Loop* loop);
+  
+  /**
+   * 更新PHI节点以适应新的前置块
+   * @param header 循环头部
+   * @param preheader 新的前置块
+   * @param oldPreds 原来的外部前驱
+   */
+  void updatePhiNodesForPreheader(BasicBlock* header, BasicBlock* preheader,
+                                 const std::vector<BasicBlock*>& oldPreds);
+  
+  /**
+   * 打印规范化统计信息
+   */
+  void printStats(Function* F);
+};
+
+} // namespace sysy

src/include/midend/Pass/Optimize/LoopStrengthReduction.h

@@ -0,0 +1,240 @@
+#pragma once
+
+#include "Pass.h"
+#include "IR.h"
+#include "LoopCharacteristics.h"
+#include "Loop.h"
+#include "Dom.h"
+#include <vector>
+#include <unordered_map>
+#include <unordered_set>
+#include <memory>
+
+namespace sysy {
+
+// 前向声明
+class LoopCharacteristicsResult;
+class LoopAnalysisResult;
+
+/**
+ * @brief 强度削弱候选项信息
+ * 记录一个可以进行强度削弱的表达式信息
+ */
+struct StrengthReductionCandidate {
+  enum OpType {
+    MULTIPLY,    // 乘法: iv * const
+    DIVIDE,      // 除法: iv / 2^n (转换为右移)
+    DIVIDE_CONST, // 除法: iv / const (使用mulh指令优化)
+    REMAINDER    // 取模: iv % 2^n (转换为位与)
+  };
+  
+  enum DivisionStrategy {
+    SIMPLE_SHIFT,     // 简单右移（仅适用于无符号或非负数）
+    SIGNED_CORRECTION, // 有符号除法修正: (x + (x >> 31) & mask) >> k
+    MULH_OPTIMIZATION  // 使用mulh指令优化任意常数除法
+  };
+  
+  Instruction* originalInst;      // 原始指令 (如 i*4, i/8, i%16)
+  Value* inductionVar;            // 归纳变量 (如 i)
+  OpType operationType;           // 操作类型
+  DivisionStrategy divStrategy;   // 除法策略（仅用于除法）
+  int multiplier;                 // 乘数/除数/模数 (如 4, 8, 16)
+  int shiftAmount;                // 位移量 (对于2的幂)
+  int offset;                     // 偏移量 (如常数项)
+  BasicBlock* containingBlock;    // 所在基本块
+  Loop* containingLoop;           // 所在循环
+  bool hasNegativeValues;         // 归纳变量是否可能为负数
+  
+  // 强度削弱后的新变量
+  PhiInst* newPhi = nullptr;      // 新的 phi 指令
+  Value* newInductionVar = nullptr; // 新的归纳变量
+  
+  StrengthReductionCandidate(Instruction* inst, Value* iv, OpType opType, int value, int off, 
+                           BasicBlock* bb, Loop* loop)
+    : originalInst(inst), inductionVar(iv), operationType(opType), 
+      divStrategy(SIMPLE_SHIFT), multiplier(value), offset(off), 
+      containingBlock(bb), containingLoop(loop), hasNegativeValues(false) {
+    
+    // 计算位移量（用于除法和取模的强度削弱）
+    if (opType == DIVIDE || opType == REMAINDER) {
+      shiftAmount = 0;
+      int temp = value;
+      while (temp > 1) {
+        temp >>= 1;
+        shiftAmount++;
+      }
+    } else {
+      shiftAmount = 0;
+    }
+  }
+};
+
+/**
+ * @brief 强度削弱上下文类
+ * 封装强度削弱优化的核心逻辑和状态
+ */
+class StrengthReductionContext {
+public:
+  StrengthReductionContext(IRBuilder* builder) : builder(builder) {}
+  
+  /**
+   * 运行强度削弱优化
+   * @param F 目标函数
+   * @param AM 分析管理器
+   * @return 是否修改了IR
+   */
+  bool run(Function* F, AnalysisManager& AM);
+
+private:
+  IRBuilder* builder;
+  
+  // 分析结果缓存
+  LoopAnalysisResult* loopAnalysis = nullptr;
+  LoopCharacteristicsResult* loopCharacteristics = nullptr;
+  DominatorTree* dominatorTree = nullptr;
+  
+  // 候选项存储
+  std::vector<std::unique_ptr<StrengthReductionCandidate>> candidates;
+  std::unordered_map<Loop*, std::vector<StrengthReductionCandidate*>> loopToCandidates;
+  
+  // ========== 核心分析和优化阶段 ==========
+  
+  /**
+   * 阶段1：识别强度削弱候选项
+   * 扫描所有循环中的乘法指令，找出可以优化的模式
+   */
+  void identifyStrengthReductionCandidates(Function* F);
+  
+  /**
+   * 阶段2：分析候选项的优化潜力
+   * 评估每个候选项的收益，过滤掉不值得优化的情况
+   */
+  void analyzeOptimizationPotential();
+  
+  /**
+   * 阶段3：执行强度削弱变换
+   * 对选中的候选项执行实际的强度削弱优化
+   */
+  bool performStrengthReduction();
+  
+  // ========== 辅助分析函数 ==========
+  
+  /**
+   * 分析归纳变量是否可能取负值
+   * @param ivInfo 归纳变量信息
+   * @param loop 所属循环
+   * @return 如果可能为负数返回true
+   */
+  bool analyzeInductionVariableRange(const InductionVarInfo* ivInfo, Loop* loop) const;
+  
+  /**
+   * 计算用于除法优化的魔数和移位量
+   * @param divisor 除数
+   * @return {魔数, 移位量}
+   */
+  std::pair<int, int> computeMulhMagicNumbers(int divisor) const;
+  
+  /**
+   * 生成除法替换代码
+   * @param candidate 优化候选项
+   * @param builder IR构建器
+   * @return 替换值
+   */
+  Value* generateDivisionReplacement(StrengthReductionCandidate* candidate, IRBuilder* builder) const;
+  
+  /**
+   * 生成任意常数除法替换代码
+   * @param candidate 优化候选项
+   * @param builder IR构建器
+   * @return 替换值
+   */
+  Value* generateConstantDivisionReplacement(StrengthReductionCandidate* candidate, IRBuilder* builder) const;
+  
+  /**
+   * 检查指令是否为强度削弱候选项
+   * @param inst 要检查的指令
+   * @param loop 所在循环
+   * @return 如果是候选项返回候选项信息，否则返回nullptr
+   */
+  std::unique_ptr<StrengthReductionCandidate> 
+  isStrengthReductionCandidate(Instruction* inst, Loop* loop);
+  
+  /**
+   * 检查值是否为循环的归纳变量
+   * @param val 要检查的值
+   * @param loop 循环
+   * @param characteristics 循环特征信息
+   * @return 如果是归纳变量返回归纳变量信息，否则返回nullptr
+   */
+  const InductionVarInfo* 
+  getInductionVarInfo(Value* val, Loop* loop, const LoopCharacteristics* characteristics);
+  
+  /**
+   * 为候选项创建新的归纳变量
+   * @param candidate 候选项
+   * @return 是否成功创建
+   */
+  bool createNewInductionVariable(StrengthReductionCandidate* candidate);
+  
+  /**
+   * 替换原始指令的所有使用
+   * @param candidate 候选项
+   * @return 是否成功替换
+   */
+  bool replaceOriginalInstruction(StrengthReductionCandidate* candidate);
+  
+  /**
+   * 估算优化收益
+   * 计算强度削弱后的性能提升
+   * @param candidate 候选项
+   * @return 估算的收益分数
+   */
+  double estimateOptimizationBenefit(const StrengthReductionCandidate* candidate);
+  
+  /**
+   * 检查优化的合法性
+   * @param candidate 候选项
+   * @return 是否可以安全地进行优化
+   */
+  bool isOptimizationLegal(const StrengthReductionCandidate* candidate);
+  
+  /**
+   * 打印调试信息
+   */
+  void printDebugInfo();
+};
+
+/**
+ * @brief 循环强度削弱优化遍
+ * 将循环中的乘法运算转换为更高效的加法运算
+ */
+class LoopStrengthReduction : public OptimizationPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+  
+  LoopStrengthReduction(IRBuilder* builder) 
+    : OptimizationPass("LoopStrengthReduction", Granularity::Function), 
+      builder(builder) {}
+  
+  /**
+   * 在函数上运行强度削弱优化
+   * @param F 目标函数
+   * @param AM 分析管理器
+   * @return 是否修改了IR
+   */
+  bool runOnFunction(Function* F, AnalysisManager& AM) override;
+  
+  /**
+   * 声明分析依赖和失效信息
+   */
+  void getAnalysisUsage(std::set<void*>& analysisDependencies, 
+                       std::set<void*>& analysisInvalidations) const override;
+  
+  void* getPassID() const override { return &ID; }
+
+private:
+  IRBuilder* builder;
+};
+
+} // namespace sysy

src/include/midend/Pass/Optimize/SCCP.h

@@ -3,6 +3,8 @@
 #include "IR.h"
 #include "Pass.h"
 #include "SysYIROptUtils.h"
+#include "AliasAnalysis.h"
+#include "SideEffectAnalysis.h"
 #include <cassert>
 #include <iostream>
 #include <map>
@@ -63,6 +65,8 @@ struct SSAPValue {
 class SCCPContext {
 private:
   IRBuilder *builder; // IR 构建器，用于插入指令和创建常量
+  AliasAnalysisResult *aliasAnalysis; // 别名分析结果
+  SideEffectAnalysisResult *sideEffectAnalysis; // 副作用分析结果
 
   // 工作列表
   // 存储需要重新评估的指令
@@ -92,6 +96,14 @@ private:
   SSAPValue ComputeConstant(BinaryInst *binaryinst, SSAPValue lhsVal, SSAPValue rhsVal);
   // 辅助函数：对一元操作进行常量折叠
   SSAPValue ComputeConstant(UnaryInst *unaryInst, SSAPValue operandVal);
+  // 辅助函数：检查是否为已知的纯函数
+  bool isKnownPureFunction(const std::string &funcName) const;
+  // 辅助函数：计算纯函数的常量结果
+  SSAPValue computePureFunctionResult(CallInst *call, const std::vector<SSAPValue> &argValues);
+  // 辅助函数：查找存储到指定位置的常量值
+  SSAPValue findStoredConstantValue(Value *ptr, BasicBlock *currentBB);
+  // 辅助函数：动态检查数组访问是否为常量索引（考虑SCCP状态）
+  bool hasRuntimeConstantAccess(Value *ptr);
 
   // 主要优化阶段
   // 阶段1: 常量传播与折叠
@@ -117,7 +129,13 @@ private:
   void RemovePhiIncoming(BasicBlock *phiParentBB, BasicBlock *removedPred);
 
 public:
-  SCCPContext(IRBuilder *builder) : builder(builder) {}
+  SCCPContext(IRBuilder *builder) : builder(builder), aliasAnalysis(nullptr), sideEffectAnalysis(nullptr) {}
+  
+  // 设置别名分析结果
+  void setAliasAnalysis(AliasAnalysisResult *aa) { aliasAnalysis = aa; }
+  
+  // 设置副作用分析结果
+  void setSideEffectAnalysis(SideEffectAnalysisResult *sea) { sideEffectAnalysis = sea; }
 
   // 运行 SCCP 优化
   void run(Function *func, AnalysisManager &AM);

src/include/midend/Pass/Pass.h

@@ -151,17 +151,21 @@ public:
     }
     AnalysisPass *analysisPass = static_cast<AnalysisPass *>(basePass.get());
 
-    if(DEBUG){
-      std::cout << "Running Analysis Pass: " << analysisPass->getName() << "\n";
-    }
     // 根据分析遍的粒度处理
     switch (analysisPass->getGranularity()) {
       case Pass::Granularity::Module: {
         // 检查是否已存在有效结果
         auto it = moduleCachedResults.find(analysisID);
         if (it != moduleCachedResults.end()) {
+          if(DEBUG) {
+            std::cout << "Using cached result for Analysis Pass: " << analysisPass->getName() << "\n";
+          }
           return static_cast<T *>(it->second.get()); // 返回缓存结果
         }
+        // 只有在实际运行时才打印调试信息
+        if(DEBUG){
+          std::cout << "Running Analysis Pass: " << analysisPass->getName() << "\n";
+        }
         // 运行模块级分析遍
         if (!pModuleRef) {
           std::cerr << "Error: Module reference not set for AnalysisManager to run Module Pass.\n";
@@ -183,8 +187,16 @@ public:
         // 检查是否已存在有效结果
         auto it = functionCachedResults.find({F, analysisID});
         if (it != functionCachedResults.end()) {
+          if(DEBUG) {
+            std::cout << "Using cached result for Analysis Pass: " << analysisPass->getName() << " (Function: " << F->getName() << ")\n";
+          }
           return static_cast<T *>(it->second.get()); // 返回缓存结果
         }
+        // 只有在实际运行时才打印调试信息
+        if(DEBUG){
+          std::cout << "Running Analysis Pass: " << analysisPass->getName() << "\n";
+          std::cout << "Function: " << F->getName() << "\n";
+        }
         // 运行函数级分析遍
         analysisPass->runOnFunction(F, *this);
         // 获取结果并缓存
@@ -202,8 +214,16 @@ public:
         // 检查是否已存在有效结果
         auto it = basicBlockCachedResults.find({BB, analysisID});
         if (it != basicBlockCachedResults.end()) {
+          if(DEBUG) {
+            std::cout << "Using cached result for Analysis Pass: " << analysisPass->getName() << " (BasicBlock: " << BB->getName() << ")\n";
+          }
           return static_cast<T *>(it->second.get()); // 返回缓存结果
         }
+        // 只有在实际运行时才打印调试信息
+        if(DEBUG){
+          std::cout << "Running Analysis Pass: " << analysisPass->getName() << "\n";
+          std::cout << "BasicBlock: " << BB->getName() << "\n";
+        }
         // 运行基本块级分析遍
         analysisPass->runOnBasicBlock(BB, *this);
         // 获取结果并缓存

src/midend/CMakeLists.txt

@@ -6,11 +6,21 @@ add_library(midend_lib STATIC
     Pass/Pass.cpp
     Pass/Analysis/Dom.cpp
     Pass/Analysis/Liveness.cpp
+    Pass/Analysis/Loop.cpp
+    Pass/Analysis/LoopCharacteristics.cpp
+    Pass/Analysis/LoopVectorization.cpp
+    Pass/Analysis/AliasAnalysis.cpp
+    Pass/Analysis/SideEffectAnalysis.cpp
+    Pass/Analysis/CallGraphAnalysis.cpp
     Pass/Optimize/DCE.cpp
     Pass/Optimize/Mem2Reg.cpp
     Pass/Optimize/Reg2Mem.cpp
     Pass/Optimize/SysYIRCFGOpt.cpp
     Pass/Optimize/SCCP.cpp
+    Pass/Optimize/LoopNormalization.cpp
+    Pass/Optimize/LICM.cpp
+    Pass/Optimize/LoopStrengthReduction.cpp
+    Pass/Optimize/InductionVariableElimination.cpp
     Pass/Optimize/BuildCFG.cpp
     Pass/Optimize/LargeArrayToGlobal.cpp
 )

src/midend/IR.cpp

@@ -762,7 +762,7 @@ void BinaryInst::print(std::ostream &os) const {
     printOperand(os, getLhs());
     os << ", ";
     printOperand(os, getRhs());
-    os << "\n  ";
+    os << "\n    ";
     printVarName(os, this) << " = zext i1 %" << tmpName << " to i32";
   } else if (kind == kFCmpEQ || kind == kFCmpNE || kind == kFCmpLT || 
              kind == kFCmpGT || kind == kFCmpLE || kind == kFCmpGE) {
@@ -777,9 +777,31 @@ void BinaryInst::print(std::ostream &os) const {
     printOperand(os, getLhs());
     os << ", ";
     printOperand(os, getRhs());
-    os << "\n  ";
+    os << "\n    ";
     printVarName(os, this) << " = zext i1 %" << tmpName << " to i32";
-  } else {
+  } else if(kind == kMulh){
+    // 模拟高位乘法：先扩展为i64，乘法，右移32位，截断为i32
+    static int mulhCount = 0;
+    mulhCount++;
+    std::string lhsName = getLhs()->getName();
+    std::string rhsName = getRhs()->getName();
+    std::string tmpLhs = "tmp_mulh_lhs_" + std::to_string(mulhCount) + "_" + lhsName;
+    std::string tmpRhs = "tmp_mulh_rhs_" + std::to_string(mulhCount) +  rhsName;
+    std::string tmpMul = "tmp_mulh_mul_" + std::to_string(mulhCount) + getName();
+    std::string tmpHigh = "tmp_mulh_high_" + std::to_string(mulhCount) + getName();
+    // printVarName(os, this) << " = "; // 输出最终变量名
+
+    // os << "; mulh emulation\n    ";
+    os << "%" << tmpLhs << " = sext i32 ";
+    printOperand(os, getLhs());
+    os << " to i64\n    ";
+    os << "%" << tmpRhs << " = sext i32 ";
+    printOperand(os, getRhs());
+    os << " to i64\n    ";
+    os << "%" << tmpMul << " = mul i64 %" << tmpLhs << ", %" << tmpRhs << "\n    ";
+    os << "%" << tmpHigh << " = ashr i64 %" << tmpMul << ", 32\n    ";
+    printVarName(os, this) << " = trunc i64 %" << tmpHigh << " to i32";
+  }else {
     // 算术和逻辑指令
     printVarName(os, this) << " = ";
     os << getKindString() << " " << *getType() << " ";

src/midend/Pass/Analysis/AliasAnalysis.cpp

@@ -0,0 +1,559 @@
+#include "AliasAnalysis.h"
+#include "SysYIRPrinter.h"
+#include <iostream>
+
+extern int DEBUG;
+
+namespace sysy {
+
+// 静态成员初始化
+void *SysYAliasAnalysisPass::ID = (void *)&SysYAliasAnalysisPass::ID;
+
+// ========== AliasAnalysisResult 实现 ==========
+
+void AliasAnalysisResult::print() const {
+    std::cout << "---- Alias Analysis Results for Function: " << AssociatedFunction->getName() << " ----\n";
+    
+    // 打印内存位置信息
+    std::cout << "  Memory Locations (" << LocationMap.size() << "):\n";
+    for (const auto& pair : LocationMap) {
+        const auto& loc = pair.second;
+        std::cout << "    - Base: " << loc->basePointer->getName();
+        std::cout << " (Type: ";
+        if (loc->isLocalArray) std::cout << "Local";
+        else if (loc->isFunctionParameter) std::cout << "Parameter";
+        else if (loc->isGlobalArray) std::cout << "Global";
+        else std::cout << "Unknown";
+        std::cout << ")\n";
+    }
+    
+    // 打印别名关系
+    std::cout << "  Alias Relations (" << AliasMap.size() << "):\n";
+    for (const auto& pair : AliasMap) {
+        std::cout << "    - (" << pair.first.first->getName() << ", " << pair.first.second->getName() << "): ";
+        switch (pair.second) {
+            case AliasType::NO_ALIAS: std::cout << "No Alias"; break;
+            case AliasType::SELF_ALIAS: std::cout << "Self Alias"; break;
+            case AliasType::POSSIBLE_ALIAS: std::cout << "Possible Alias"; break;
+            case AliasType::UNKNOWN_ALIAS: std::cout << "Unknown Alias"; break;
+        }
+        std::cout << "\n";
+    }
+    std::cout << "-----------------------------------------------------------\n";
+}
+
+AliasType AliasAnalysisResult::queryAlias(Value* ptr1, Value* ptr2) const {
+  auto key = std::make_pair(ptr1, ptr2);
+  auto it = AliasMap.find(key);
+  if (it != AliasMap.end()) {
+    return it->second;
+  }
+  
+  // 尝试反向查找
+  key = std::make_pair(ptr2, ptr1);
+  it = AliasMap.find(key);
+  if (it != AliasMap.end()) {
+    return it->second;
+  }
+  
+  return AliasType::UNKNOWN_ALIAS; // 保守估计
+}
+
+const MemoryLocation* AliasAnalysisResult::getMemoryLocation(Value* ptr) const {
+  auto it = LocationMap.find(ptr);
+  return (it != LocationMap.end()) ? it->second.get() : nullptr;
+}
+
+bool AliasAnalysisResult::isLocalArray(Value* ptr) const {
+  const MemoryLocation* loc = getMemoryLocation(ptr);
+  return loc && loc->isLocalArray;
+}
+
+bool AliasAnalysisResult::isFunctionParameter(Value* ptr) const {
+  const MemoryLocation* loc = getMemoryLocation(ptr);
+  return loc && loc->isFunctionParameter;
+}
+
+bool AliasAnalysisResult::isGlobalArray(Value* ptr) const {
+  const MemoryLocation* loc = getMemoryLocation(ptr);
+  return loc && loc->isGlobalArray;
+}
+
+bool AliasAnalysisResult::hasConstantAccess(Value* ptr) const {
+  const MemoryLocation* loc = getMemoryLocation(ptr);
+  return loc && loc->hasConstantIndices;
+}
+
+AliasAnalysisResult::Statistics AliasAnalysisResult::getStatistics() const {
+  Statistics stats = {0};
+  
+  stats.totalQueries = AliasMap.size();
+  
+  for (auto& pair : AliasMap) {
+    switch (pair.second) {
+      case AliasType::NO_ALIAS: stats.noAlias++; break;
+      case AliasType::SELF_ALIAS: stats.selfAlias++; break;
+      case AliasType::POSSIBLE_ALIAS: stats.possibleAlias++; break;
+      case AliasType::UNKNOWN_ALIAS: stats.unknownAlias++; break;
+    }
+  }
+  
+  for (auto& loc : LocationMap) {
+    if (loc.second->isLocalArray) stats.localArrays++;
+    if (loc.second->isFunctionParameter) stats.functionParameters++;
+    if (loc.second->isGlobalArray) stats.globalArrays++;
+    if (loc.second->hasConstantIndices) stats.constantAccesses++;
+  }
+  
+  return stats;
+}
+
+void AliasAnalysisResult::printStatics() const {
+  std::cout << "=== Alias Analysis Results ===" << std::endl;
+  
+  auto stats = getStatistics();
+  std::cout << "Total queries: " << stats.totalQueries << std::endl;
+  std::cout << "No alias: " << stats.noAlias << std::endl;
+  std::cout << "Self alias: " << stats.selfAlias << std::endl;
+  std::cout << "Possible alias: " << stats.possibleAlias << std::endl;
+  std::cout << "Unknown alias: " << stats.unknownAlias << std::endl;
+  std::cout << "Local arrays: " << stats.localArrays << std::endl;
+  std::cout << "Function parameters: " << stats.functionParameters << std::endl;
+  std::cout << "Global arrays: " << stats.globalArrays << std::endl;
+  std::cout << "Constant accesses: " << stats.constantAccesses << std::endl;
+}
+
+void AliasAnalysisResult::addMemoryLocation(std::unique_ptr<MemoryLocation> location) {
+  Value* ptr = location->accessPointer;
+  LocationMap[ptr] = std::move(location);
+}
+
+void AliasAnalysisResult::addAliasRelation(Value* ptr1, Value* ptr2, AliasType type) {
+  auto key = std::make_pair(ptr1, ptr2);
+  AliasMap[key] = type;
+}
+
+// ========== SysYAliasAnalysisPass 实现 ==========
+
+bool SysYAliasAnalysisPass::runOnFunction(Function *F, AnalysisManager &AM) {
+  if (DEBUG) {
+    std::cout << "Running SysY Alias Analysis on function: " << F->getName() << std::endl;
+  }
+  
+  // 创建分析结果
+  CurrentResult = std::make_unique<AliasAnalysisResult>(F);
+  
+  // 执行主要分析步骤
+  collectMemoryAccesses(F);
+  buildAliasRelations(F);
+  optimizeForSysY(F);
+  
+  if (DEBUG) {
+    CurrentResult->print();
+    CurrentResult->printStatics();
+  }
+
+  return false; // 分析遍不修改IR
+}
+
+void SysYAliasAnalysisPass::collectMemoryAccesses(Function* F) {
+  // 收集函数中所有内存访问指令
+  for (auto& bb : F->getBasicBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      Value* ptr = nullptr;
+      
+      if (auto* loadInst = dynamic_cast<LoadInst*>(inst.get())) {
+        ptr = loadInst->getPointer();
+      } else if (auto* storeInst = dynamic_cast<StoreInst*>(inst.get())) {
+        ptr = storeInst->getPointer();
+      }
+      
+      if (ptr) {
+        // 创建内存位置信息
+        auto location = createMemoryLocation(ptr);
+        location->accessInsts.push_back(inst.get());
+        
+        // 更新读写标记
+        if (dynamic_cast<LoadInst*>(inst.get())) {
+          location->hasReads = true;
+        } else {
+          location->hasWrites = true;
+        }
+        
+        CurrentResult->addMemoryLocation(std::move(location));
+      }
+    }
+  }
+}
+
+void SysYAliasAnalysisPass::buildAliasRelations(Function *F) {
+  // 构建所有内存访问之间的别名关系
+  auto& locationMap = CurrentResult->LocationMap;
+  
+  std::vector<Value*> allPointers;
+  for (auto& pair : locationMap) {
+    allPointers.push_back(pair.first);
+  }
+  
+  // 两两比较所有指针
+  for (size_t i = 0; i < allPointers.size(); ++i) {
+    for (size_t j = i + 1; j < allPointers.size(); ++j) {
+      Value* ptr1 = allPointers[i];
+      Value* ptr2 = allPointers[j];
+      
+      MemoryLocation* loc1 = locationMap[ptr1].get();
+      MemoryLocation* loc2 = locationMap[ptr2].get();
+      
+      AliasType aliasType = analyzeAliasBetween(loc1, loc2);
+      CurrentResult->addAliasRelation(ptr1, ptr2, aliasType);
+    }
+  }
+}
+
+void SysYAliasAnalysisPass::optimizeForSysY(Function* F) {
+  // SysY特化优化
+  applySysYConstraints(F);
+  optimizeParameterAnalysis(F);
+  optimizeArrayAccessAnalysis(F);
+}
+
+std::unique_ptr<MemoryLocation> SysYAliasAnalysisPass::createMemoryLocation(Value* ptr) {
+  Value* basePtr = getBasePointer(ptr);
+  auto location = std::make_unique<MemoryLocation>(basePtr, ptr);
+  
+  // 分析内存类型和索引模式
+  analyzeMemoryType(location.get());
+  analyzeIndexPattern(location.get());
+  
+  return location;
+}
+
+Value* SysYAliasAnalysisPass::getBasePointer(Value* ptr) {
+  // 递归剥离GEP指令，找到真正的基指针
+  if (auto* gepInst = dynamic_cast<GetElementPtrInst*>(ptr)) {
+    return getBasePointer(gepInst->getBasePointer());
+  }
+  return ptr;
+}
+
+void SysYAliasAnalysisPass::analyzeMemoryType(MemoryLocation* location) {
+  Value* base = location->basePointer;
+  
+  // 检查内存类型
+  if (dynamic_cast<AllocaInst*>(base)) {
+    location->isLocalArray = true;
+  } else if (dynamic_cast<Argument*>(base)) {
+    location->isFunctionParameter = true;
+  } else if (dynamic_cast<GlobalValue*>(base)) {
+    location->isGlobalArray = true;
+  }
+}
+
+void SysYAliasAnalysisPass::analyzeIndexPattern(MemoryLocation* location) {
+  // 分析GEP指令的索引模式
+  if (auto* gepInst = dynamic_cast<GetElementPtrInst*>(location->accessPointer)) {
+    // 初始化为true，如果发现非常量索引则设为false
+    location->hasConstantIndices = true;
+    
+    // 收集所有索引
+    for (unsigned i = 0; i < gepInst->getNumIndices(); ++i) {
+      Value* index = gepInst->getIndex(i);
+      location->indices.push_back(index);
+      
+      // 检查是否为常量索引
+      if (!isConstantValue(index)) {
+        location->hasConstantIndices = false;
+      }
+    }
+    
+    // 检查是否包含循环变量
+    Function* containingFunc = nullptr;
+    if (auto* inst = dynamic_cast<Instruction*>(location->basePointer)) {
+      containingFunc = inst->getParent()->getParent();
+    } else if (auto* arg = dynamic_cast<Argument*>(location->basePointer)) {
+      containingFunc = arg->getParent();
+    }
+    
+    if (containingFunc) {
+      location->hasLoopVariableIndex = hasLoopVariableInIndices(location->indices, containingFunc);
+    }
+    
+    // 计算常量偏移
+    if (location->hasConstantIndices) {
+      location->constantOffset = calculateConstantOffset(location->indices);
+    }
+  }
+}
+
+AliasType SysYAliasAnalysisPass::analyzeAliasBetween(MemoryLocation* loc1, MemoryLocation* loc2) {
+  // 分析两个内存位置之间的别名关系
+  
+  // 1. 相同基指针的情况需要进一步分析索引
+  if (loc1->basePointer == loc2->basePointer) {
+    // 如果是同一个访问指针，那就是完全相同的内存位置
+    if (loc1->accessPointer == loc2->accessPointer) {
+      return AliasType::SELF_ALIAS;
+    }
+    
+    // 相同基指针但不同访问指针，需要比较索引
+    return compareIndices(loc1, loc2);
+  }
+  
+  // 2. 不同类型的内存位置
+  if ((loc1->isLocalArray && loc2->isLocalArray)) {
+    return compareLocalArrays(loc1, loc2);
+  }
+  
+  if ((loc1->isFunctionParameter && loc2->isFunctionParameter)) {
+    return compareParameters(loc1, loc2);
+  }
+  
+  if ((loc1->isGlobalArray || loc2->isGlobalArray)) {
+    return compareWithGlobal(loc1, loc2);
+  }
+  
+  return compareMixedTypes(loc1, loc2);
+}
+
+AliasType SysYAliasAnalysisPass::compareIndices(MemoryLocation* loc1, MemoryLocation* loc2) {
+  // 比较相同基指针下的不同索引访问
+  
+  // 如果都有常量索引，可以精确比较
+  if (loc1->hasConstantIndices && loc2->hasConstantIndices) {
+    // 比较索引数量
+    if (loc1->indices.size() != loc2->indices.size()) {
+      return AliasType::NO_ALIAS;
+    }
+    
+    // 逐个比较索引值
+    for (size_t i = 0; i < loc1->indices.size(); ++i) {
+      Value* idx1 = loc1->indices[i];
+      Value* idx2 = loc2->indices[i];
+      
+      // 都是常量，比较值
+      auto* const1 = dynamic_cast<ConstantInteger*>(idx1);
+      auto* const2 = dynamic_cast<ConstantInteger*>(idx2);
+      
+      if (const1 && const2) {
+        int val1 = std::get<int>(const1->getVal());
+        int val2 = std::get<int>(const2->getVal());
+        
+        if (val1 != val2) {
+          return AliasType::NO_ALIAS;  // 不同常量索引，确定无别名
+        }
+      } else {
+        // 不是常量，无法确定
+        return AliasType::POSSIBLE_ALIAS;
+      }
+    }
+    
+    // 所有索引都相同
+    return AliasType::SELF_ALIAS;
+  }
+  
+  // 如果有非常量索引，保守估计
+  return AliasType::POSSIBLE_ALIAS;
+}
+
+AliasType SysYAliasAnalysisPass::compareLocalArrays(MemoryLocation* loc1, MemoryLocation* loc2) {
+  // 不同局部数组不别名
+  return AliasType::NO_ALIAS;
+}
+
+AliasType SysYAliasAnalysisPass::compareParameters(MemoryLocation* loc1, MemoryLocation* loc2) {
+  // SysY特化：可配置的数组参数别名策略
+  // 
+  // SysY中数组参数的语法形式：
+  //   void func(int a[], int b[])     - 一维数组参数
+  //   void func(int a[][10], int b[]) - 多维数组参数
+  //
+  // 默认保守策略：不同数组参数可能别名（因为可能传入相同数组）
+  //   func(arr, arr);  // 传入同一个数组给两个参数
+  //
+  // 激进策略：假设不同数组参数不会传入相同数组（适用于评测环境）
+  //   在SysY评测中，这种情况很少出现
+  
+  if (useAggressiveParameterAnalysis()) {
+    // 激进策略：不同数组参数假设不别名
+    return AliasType::NO_ALIAS;
+  } else {
+    // 保守策略：不同数组参数可能别名
+    return AliasType::POSSIBLE_ALIAS;
+  }
+}
+
+AliasType SysYAliasAnalysisPass::compareWithGlobal(MemoryLocation* loc1, MemoryLocation* loc2) {
+  // 涉及全局数组的访问分析
+  // 这里处理所有涉及全局数组的情况
+  
+  // SysY特化：局部数组与全局数组不别名
+  if ((loc1->isLocalArray && loc2->isGlobalArray) || 
+      (loc1->isGlobalArray && loc2->isLocalArray)) {
+    // 局部数组在栈上，全局数组在全局区，确定不别名
+    return AliasType::NO_ALIAS;
+  }
+  
+  // SysY特化：数组参数与全局数组可能别名（保守处理）
+  if ((loc1->isFunctionParameter && loc2->isGlobalArray) || 
+      (loc1->isGlobalArray && loc2->isFunctionParameter)) {
+    // 数组参数可能指向全局数组，需要保守处理
+    return AliasType::POSSIBLE_ALIAS;
+  }
+  
+  // 其他涉及全局数组的情况，采用保守策略
+  return AliasType::POSSIBLE_ALIAS;
+}
+
+AliasType SysYAliasAnalysisPass::compareMixedTypes(MemoryLocation* loc1, MemoryLocation* loc2) {
+  // 混合类型访问的别名分析
+  // 处理不同内存类型之间的别名关系
+  
+  // SysY特化：局部数组与数组参数通常不别名
+  // 典型场景：
+  //   void func(int p[]) {       // p 是数组参数
+  //       int local[10];         // local 是局部数组
+  //       p[0] = local[0];       // 混合类型访问
+  //   }
+  // 或多维数组：
+  //   void func(int p[][10]) {   // p 是多维数组参数
+  //       int local[10];         // local 是局部数组
+  //       p[i][0] = local[0];    // 混合类型访问
+  //   } 
+  // 局部数组与数组参数：在SysY中通常不别名
+  if ((loc1->isLocalArray && loc2->isFunctionParameter) || 
+      (loc1->isFunctionParameter && loc2->isLocalArray)) {
+    // 因为局部数组是栈上分配，而数组参数是传入的外部数组
+    return AliasType::NO_ALIAS;
+  }
+
+  // 对于其他混合情况，保守估计
+  return AliasType::UNKNOWN_ALIAS;
+}
+
+void SysYAliasAnalysisPass::applySysYConstraints(Function* F) {
+  // SysY语言特定的约束和优化
+  // 1. SysY没有指针运算，简化了别名分析
+  // 2. 数组传参时保持数组语义
+  // 3. 没有动态内存分配，所有数组要么是局部的要么是参数/全局
+}
+
+void SysYAliasAnalysisPass::optimizeParameterAnalysis(Function* F) {
+  // 数组参数别名分析优化
+  // 为SysY评测环境提供可配置的优化策略
+  
+  if (!enableParameterOptimization()) {
+    return; // 保持默认的保守策略
+  }
+  
+  // 可选的参数优化：假设不同数组参数不会传入相同数组
+  // 典型的SysY函数调用：
+  //   int arr1[10], arr2[20];
+  //   func(arr1, arr2);  // 传入不同数组
+  // 而不是：
+  //   func(arr1, arr1);  // 传入相同数组给两个参数
+  // 这在SysY评测中通常是安全的假设
+  auto& locationMap = CurrentResult->LocationMap;
+  
+  for (auto it1 = locationMap.begin(); it1 != locationMap.end(); ++it1) {
+    for (auto it2 = std::next(it1); it2 != locationMap.end(); ++it2) {
+      MemoryLocation* loc1 = it1->second.get();
+      MemoryLocation* loc2 = it2->second.get();
+      
+      // 如果两个都是数组参数且基指针不同，设为NO_ALIAS
+      if (loc1->isFunctionParameter && loc2->isFunctionParameter && 
+          loc1->basePointer != loc2->basePointer) {
+        CurrentResult->addAliasRelation(it1->first, it2->first, AliasType::NO_ALIAS);
+      }
+    }
+  }
+}
+
+void SysYAliasAnalysisPass::optimizeArrayAccessAnalysis(Function* F) {
+  // 数组访问别名分析优化
+  // 基于SysY语言的特点进行简单优化
+  
+  // 优化1：同一数组的不同常量索引访问确定无别名
+  optimizeConstantIndexAccesses();
+  
+  // 优化2：识别简单的顺序访问模式
+  optimizeSequentialAccesses();
+}
+
+bool SysYAliasAnalysisPass::isConstantValue(Value* val) {
+  return dynamic_cast<ConstantInteger*>(val) != nullptr; // 简化，只检查整数常量
+}
+
+bool SysYAliasAnalysisPass::hasLoopVariableInIndices(const std::vector<Value*>& indices, Function* F) {
+  // 保守策略：所有非常量索引都视为可能的循环变量
+  // 这样可以避免复杂的循环分析依赖，保持分析的独立性
+  for (Value* index : indices) {
+    if (!isConstantValue(index)) {
+      return true; // 保守估计，确保正确性
+    }
+  }
+  return false;
+}
+
+int SysYAliasAnalysisPass::calculateConstantOffset(const std::vector<Value*>& indices) {
+  int offset = 0;
+  for (Value* index : indices) {
+    if (auto* constInt = dynamic_cast<ConstantInteger*>(index)) {
+      // ConstantInteger的getVal()返回variant，需要提取int值
+      auto val = constInt->getVal();
+      if (std::holds_alternative<int>(val)) {
+        offset += std::get<int>(val);
+      }
+    }
+  }
+  return offset;
+}
+
+void SysYAliasAnalysisPass::printStatistics() const {
+  if (CurrentResult) {
+    CurrentResult->print();
+  }
+}
+
+void SysYAliasAnalysisPass::optimizeConstantIndexAccesses() {
+  // 优化常量索引访问的别名关系
+  // 对于相同基指针的访问，如果索引都是常量且不同，则确定无别名
+  
+  auto& locationMap = CurrentResult->LocationMap;
+  std::vector<Value*> allPointers;
+  for (auto& pair : locationMap) {
+    allPointers.push_back(pair.first);
+  }
+  
+  for (size_t i = 0; i < allPointers.size(); ++i) {
+    for (size_t j = i + 1; j < allPointers.size(); ++j) {
+      Value* ptr1 = allPointers[i];
+      Value* ptr2 = allPointers[j];
+      MemoryLocation* loc1 = locationMap[ptr1].get();
+      MemoryLocation* loc2 = locationMap[ptr2].get();
+      
+      // 相同基指针且都有常量索引
+      if (loc1->basePointer == loc2->basePointer && 
+          loc1->hasConstantIndices && loc2->hasConstantIndices) {
+        
+        // 比较常量偏移
+        if (loc1->constantOffset != loc2->constantOffset) {
+          // 不同的常量偏移，确定无别名
+          CurrentResult->addAliasRelation(ptr1, ptr2, AliasType::NO_ALIAS);
+        }
+      }
+    }
+  }
+}
+
+void SysYAliasAnalysisPass::optimizeSequentialAccesses() {
+  // 识别和优化顺序访问模式
+  // 这是一个简化的实现，主要用于识别数组的顺序遍历
+  
+  // 在SysY中，大多数数组访问都是通过循环进行的
+  // 对于非常量索引的访问，我们采用保守策略，不进行过多优化
+  // 这样可以保持分析的简单性和正确性
+  
+  // 未来如果需要更精确的分析，可以在这里添加更复杂的逻辑
+}
+
+} // namespace sysy

src/midend/Pass/Analysis/CallGraphAnalysis.cpp

@@ -0,0 +1,417 @@
+#include "CallGraphAnalysis.h"
+#include "SysYIRPrinter.h"
+#include <iostream>
+#include <stack>
+#include <unordered_set>
+
+extern int DEBUG;
+
+namespace sysy {
+
+// 静态成员初始化
+void* CallGraphAnalysisPass::ID = (void*)&CallGraphAnalysisPass::ID;
+
+// ========== CallGraphAnalysisResult 实现 ==========
+
+CallGraphAnalysisResult::Statistics CallGraphAnalysisResult::getStatistics() const {
+    Statistics stats = {};
+    stats.totalFunctions = nodes.size();
+    
+    size_t totalCallEdges = 0;
+    size_t recursiveFunctions = 0;
+    size_t selfRecursiveFunctions = 0;
+    size_t totalCallers = 0;
+    size_t totalCallees = 0;
+    
+    for (const auto& pair : nodes) {
+        const auto& node = pair.second;
+        totalCallEdges += node->callees.size();
+        totalCallers += node->callers.size();
+        totalCallees += node->callees.size();
+        
+        if (node->isRecursive) recursiveFunctions++;
+        if (node->isSelfRecursive) selfRecursiveFunctions++;
+    }
+    
+    stats.totalCallEdges = totalCallEdges;
+    stats.recursiveFunctions = recursiveFunctions;
+    stats.selfRecursiveFunctions = selfRecursiveFunctions;
+    stats.stronglyConnectedComponents = sccs.size();
+    
+    // 计算最大SCC大小
+    size_t maxSCCSize = 0;
+    for (const auto& scc : sccs) {
+        maxSCCSize = std::max(maxSCCSize, scc.size());
+    }
+    stats.maxSCCSize = maxSCCSize;
+    
+    // 计算平均值
+    if (stats.totalFunctions > 0) {
+        stats.avgCallersPerFunction = static_cast<double>(totalCallers) / stats.totalFunctions;
+        stats.avgCalleesPerFunction = static_cast<double>(totalCallees) / stats.totalFunctions;
+    }
+    
+    return stats;
+}
+
+void CallGraphAnalysisResult::print() const {
+    std::cout << "---- Call Graph Analysis Results for Module ----\n";
+    
+    // 打印基本统计信息
+    auto stats = getStatistics();
+    std::cout << "  Statistics:\n";
+    std::cout << "    Total Functions: " << stats.totalFunctions << "\n";
+    std::cout << "    Total Call Edges: " << stats.totalCallEdges << "\n";
+    std::cout << "    Recursive Functions: " << stats.recursiveFunctions << "\n";
+    std::cout << "    Self-Recursive Functions: " << stats.selfRecursiveFunctions << "\n";
+    std::cout << "    Strongly Connected Components: " << stats.stronglyConnectedComponents << "\n";
+    std::cout << "    Max SCC Size: " << stats.maxSCCSize << "\n";
+    std::cout << "    Avg Callers per Function: " << stats.avgCallersPerFunction << "\n";
+    std::cout << "    Avg Callees per Function: " << stats.avgCalleesPerFunction << "\n";
+    
+    // 打印拓扑排序结果
+    std::cout << "  Topological Order (" << topologicalOrder.size() << "):\n";
+    for (size_t i = 0; i < topologicalOrder.size(); ++i) {
+        std::cout << "    " << i << ": " << topologicalOrder[i]->getName() << "\n";
+    }
+    
+    // 打印强连通分量
+    if (!sccs.empty()) {
+        std::cout << "  Strongly Connected Components:\n";
+        for (size_t i = 0; i < sccs.size(); ++i) {
+            std::cout << "    SCC " << i << " (size " << sccs[i].size() << "): ";
+            for (size_t j = 0; j < sccs[i].size(); ++j) {
+                if (j > 0) std::cout << ", ";
+                std::cout << sccs[i][j]->getName();
+            }
+            std::cout << "\n";
+        }
+    }
+    
+    // 打印每个函数的详细信息
+    std::cout << "  Function Details:\n";
+    for (const auto& pair : nodes) {
+        const auto& node = pair.second;
+        std::cout << "    Function: " << node->function->getName();
+        
+        if (node->isRecursive) {
+            std::cout << " (Recursive";
+            if (node->isSelfRecursive) std::cout << ", Self";
+            if (node->recursiveDepth >= 0) std::cout << ", Depth=" << node->recursiveDepth;
+            std::cout << ")";
+        }
+        std::cout << "\n";
+        
+        if (!node->callers.empty()) {
+            std::cout << "      Callers (" << node->callers.size() << "): ";
+            bool first = true;
+            for (Function* caller : node->callers) {
+                if (!first) std::cout << ", ";
+                std::cout << caller->getName();
+                first = false;
+            }
+            std::cout << "\n";
+        }
+        
+        if (!node->callees.empty()) {
+            std::cout << "      Callees (" << node->callees.size() << "): ";
+            bool first = true;
+            for (Function* callee : node->callees) {
+                if (!first) std::cout << ", ";
+                std::cout << callee->getName();
+                first = false;
+            }
+            std::cout << "\n";
+        }
+    }
+    
+    std::cout << "--------------------------------------------------\n";
+}
+
+void CallGraphAnalysisResult::addNode(Function* F) {
+    if (nodes.find(F) == nodes.end()) {
+        nodes[F] = std::make_unique<CallGraphNode>(F);
+    }
+}
+
+void CallGraphAnalysisResult::addCallEdge(Function* caller, Function* callee) {
+    // 确保两个函数都有对应的节点
+    addNode(caller);
+    addNode(callee);
+    
+    // 添加调用边
+    nodes[caller]->callees.insert(callee);
+    nodes[callee]->callers.insert(caller);
+    
+    // 更新统计信息
+    nodes[caller]->totalCallees = nodes[caller]->callees.size();
+    nodes[callee]->totalCallers = nodes[callee]->callers.size();
+    
+    // 检查自递归
+    if (caller == callee) {
+        nodes[caller]->isSelfRecursive = true;
+        nodes[caller]->isRecursive = true;
+    }
+}
+
+void CallGraphAnalysisResult::computeTopologicalOrder() {
+    topologicalOrder.clear();
+    std::unordered_set<Function*> visited;
+    
+    // 对每个未访问的函数进行DFS
+    for (const auto& pair : nodes) {
+        Function* F = pair.first;
+        if (visited.find(F) == visited.end()) {
+            dfsTopological(F, visited, topologicalOrder);
+        }
+    }
+    
+    // 反转结果（因为我们在后序遍历中添加）
+    std::reverse(topologicalOrder.begin(), topologicalOrder.end());
+}
+
+void CallGraphAnalysisResult::dfsTopological(Function* F, std::unordered_set<Function*>& visited, 
+                                            std::vector<Function*>& result) {
+    visited.insert(F);
+    
+    auto node = getNode(F);
+    if (node) {
+        // 先访问所有被调用的函数
+        for (Function* callee : node->callees) {
+            if (visited.find(callee) == visited.end()) {
+                dfsTopological(callee, visited, result);
+            }
+        }
+    }
+    
+    // 后序遍历：访问完所有子节点后添加当前节点
+    result.push_back(F);
+}
+
+void CallGraphAnalysisResult::computeStronglyConnectedComponents() {
+    tarjanSCC();
+    
+    // 为每个函数设置其所属的SCC
+    functionToSCC.clear();
+    for (size_t i = 0; i < sccs.size(); ++i) {
+        for (Function* F : sccs[i]) {
+            functionToSCC[F] = static_cast<int>(i);
+        }
+    }
+}
+
+void CallGraphAnalysisResult::tarjanSCC() {
+    sccs.clear();
+    
+    std::vector<int> indices(nodes.size(), -1);
+    std::vector<int> lowlinks(nodes.size(), -1);
+    std::vector<Function*> stack;
+    std::unordered_set<Function*> onStack;
+    int index = 0;
+    
+    // 为函数分配索引
+    std::map<Function*, int> functionIndex;
+    int idx = 0;
+    for (const auto& pair : nodes) {
+        functionIndex[pair.first] = idx++;
+    }
+    
+    // 对每个未访问的函数运行Tarjan算法
+    for (const auto& pair : nodes) {
+        Function* F = pair.first;
+        int fIdx = functionIndex[F];
+        if (indices[fIdx] == -1) {
+            tarjanDFS(F, index, indices, lowlinks, stack, onStack);
+        }
+    }
+}
+
+void CallGraphAnalysisResult::tarjanDFS(Function* F, int& index, std::vector<int>& indices, 
+                                      std::vector<int>& lowlinks, std::vector<Function*>& stack, 
+                                      std::unordered_set<Function*>& onStack) {
+    // 这里需要函数到索引的映射，简化实现
+    // 在实际实现中应该维护一个全局的函数索引映射
+    static std::map<Function*, int> functionIndex;
+    static int nextIndex = 0;
+    
+    if (functionIndex.find(F) == functionIndex.end()) {
+        functionIndex[F] = nextIndex++;
+    }
+    
+    int fIdx = functionIndex[F];
+    
+    // 确保向量足够大
+    if (fIdx >= static_cast<int>(indices.size())) {
+        indices.resize(fIdx + 1, -1);
+        lowlinks.resize(fIdx + 1, -1);
+    }
+    
+    indices[fIdx] = index;
+    lowlinks[fIdx] = index;
+    index++;
+    
+    stack.push_back(F);
+    onStack.insert(F);
+    
+    auto node = getNode(F);
+    if (node) {
+        for (Function* callee : node->callees) {
+            int calleeIdx = functionIndex[callee];
+            
+            // 确保向量足够大
+            if (calleeIdx >= static_cast<int>(indices.size())) {
+                indices.resize(calleeIdx + 1, -1);
+                lowlinks.resize(calleeIdx + 1, -1);
+            }
+            
+            if (indices[calleeIdx] == -1) {
+                // 递归访问
+                tarjanDFS(callee, index, indices, lowlinks, stack, onStack);
+                lowlinks[fIdx] = std::min(lowlinks[fIdx], lowlinks[calleeIdx]);
+            } else if (onStack.find(callee) != onStack.end()) {
+                // 后向边
+                lowlinks[fIdx] = std::min(lowlinks[fIdx], indices[calleeIdx]);
+            }
+        }
+    }
+    
+    // 如果F是SCC的根
+    if (lowlinks[fIdx] == indices[fIdx]) {
+        std::vector<Function*> scc;
+        Function* w;
+        do {
+            w = stack.back();
+            stack.pop_back();
+            onStack.erase(w);
+            scc.push_back(w);
+        } while (w != F);
+        
+        sccs.push_back(std::move(scc));
+    }
+}
+
+void CallGraphAnalysisResult::analyzeRecursion() {
+    // 基于SCC分析递归
+    for (const auto& scc : sccs) {
+        if (scc.size() > 1) {
+            // 多函数的SCC，标记为相互递归
+            for (Function* F : scc) {
+                auto* node = getMutableNode(F);
+                if (node) {
+                    node->isRecursive = true;
+                    node->recursiveDepth = -1; // 相互递归，深度未定义
+                }
+            }
+        } else if (scc.size() == 1) {
+            // 单函数SCC，检查是否自递归
+            Function* F = scc[0];
+            auto* node = getMutableNode(F);
+            if (node && node->callees.count(F) > 0) {
+                node->isSelfRecursive = true;
+                node->isRecursive = true;
+                node->recursiveDepth = -1; // 简化：不计算递归深度
+            }
+        }
+    }
+}
+
+// ========== CallGraphAnalysisPass 实现 ==========
+
+bool CallGraphAnalysisPass::runOnModule(Module* M, AnalysisManager& AM) {
+    if (DEBUG) {
+        std::cout << "Running Call Graph Analysis on module\n";
+    }
+    
+    // 创建分析结果
+    CurrentResult = std::make_unique<CallGraphAnalysisResult>(M);
+    
+    // 执行主要分析步骤
+    buildCallGraph(M);
+    CurrentResult->computeTopologicalOrder();
+    CurrentResult->computeStronglyConnectedComponents();
+    CurrentResult->analyzeRecursion();
+    
+    if (DEBUG) {
+        CurrentResult->print();
+    }
+    
+    return false; // 分析遍不修改IR
+}
+
+void CallGraphAnalysisPass::buildCallGraph(Module* M) {
+    // 1. 为所有函数创建节点（包括声明但未定义的函数）
+    for (auto& pair : M->getFunctions()) {
+        Function* F = pair.second.get();
+        if (!isLibraryFunction(F) && !isIntrinsicFunction(F)) {
+            CurrentResult->addNode(F);
+        }
+    }
+    
+    // 2. 扫描所有函数的调用关系
+    for (auto& pair : M->getFunctions()) {
+        Function* F = pair.second.get();
+        if (!isLibraryFunction(F) && !isIntrinsicFunction(F)) {
+            scanFunctionCalls(F);
+        }
+    }
+}
+
+void CallGraphAnalysisPass::scanFunctionCalls(Function* F) {
+    // 遍历函数中的所有基本块和指令
+    for (auto& BB : F->getBasicBlocks_NoRange()) {
+        for (auto& I : BB->getInstructions()) {
+            if (CallInst* call = dynamic_cast<CallInst*>(I.get())) {
+                processCallInstruction(call, F);
+            }
+        }
+    }
+}
+
+void CallGraphAnalysisPass::processCallInstruction(CallInst* call, Function* caller) {
+    Function* callee = call->getCallee();
+    
+    if (!callee) {
+        // 间接调用，无法静态确定目标函数
+        return;
+    }
+    
+    if (isLibraryFunction(callee) || isIntrinsicFunction(callee)) {
+        // 跳过标准库函数和内置函数
+        return;
+    }
+    
+    // 添加调用边
+    CurrentResult->addCallEdge(caller, callee);
+    
+    // 更新调用点统计
+    auto* node = CurrentResult->getMutableNode(caller);
+    if (node) {
+        node->callSiteCount++;
+    }
+}
+
+bool CallGraphAnalysisPass::isLibraryFunction(Function* F) const {
+    std::string name = F->getName();
+    
+    // SysY标准库函数
+    return name == "getint" || name == "getch" || name == "getfloat" ||
+           name == "getarray" || name == "getfarray" ||
+           name == "putint" || name == "putch" || name == "putfloat" ||
+           name == "putarray" || name == "putfarray" ||
+           name == "_sysy_starttime" || name == "_sysy_stoptime";
+}
+
+bool CallGraphAnalysisPass::isIntrinsicFunction(Function* F) const {
+    std::string name = F->getName();
+    
+    // 编译器内置函数（后续可以增加某些内置函数）
+    return name.substr(0, 5) == "llvm." || name.substr(0, 5) == "sysy.";
+}
+
+void CallGraphAnalysisPass::printStatistics() const {
+    if (CurrentResult) {
+        CurrentResult->print();
+    }
+}
+
+} // namespace sysy

src/midend/Pass/Analysis/Loop.cpp

@@ -0,0 +1,415 @@
+#include "Dom.h" // 确保包含 DominatorTreeAnalysisPass 的定义
+#include "Loop.h" //
+#include "AliasAnalysis.h" // 添加别名分析依赖
+#include "SideEffectAnalysis.h" // 添加副作用分析依赖
+#include <iostream>
+#include <queue> // 用于 BFS 遍历设置循环层级
+
+// 调试模式开关
+#ifndef DEBUG
+#define DEBUG 0
+#endif
+
+namespace sysy {
+
+// 定义 Pass 的唯一 ID
+void *LoopAnalysisPass::ID = (void *)&LoopAnalysisPass::ID;
+
+// 定义 Loop 类的静态变量
+int Loop::NextLoopID = 0;
+// **实现 LoopAnalysisResult::print() 方法**
+
+
+void LoopAnalysisResult::printBBSet(const std::string &prefix, const std::set<BasicBlock *> &s) const{
+  if (!DEBUG) return;
+  std::cout << prefix << "{";
+  bool first = true;
+  for (const auto &bb : s) {
+    if (!first) std::cout << ", ";
+    std::cout << bb->getName();
+    first = false;
+  }
+  std::cout << "}";
+}
+
+// **辅助函数：打印 Loop 指针向量**
+void LoopAnalysisResult::printLoopVector(const std::string &prefix, const std::vector<Loop *> &loops) const {
+  if (!DEBUG) return;
+  std::cout << prefix << "[";
+  bool first = true;
+  for (const auto &loop : loops) {
+    if (!first) std::cout << ", ";
+    std::cout << loop->getName(); // 假设 Loop::getName() 存在
+    first = false;
+  }
+  std::cout << "]";
+}
+
+void LoopAnalysisResult::print() const {
+  if (!DEBUG) return; // 只有在 DEBUG 模式下才打印
+
+  std::cout << "\n--- Loop Analysis Results for Function: " << AssociatedFunction->getName() << " ---" << std::endl;
+
+  if (AllLoops.empty()) {
+    std::cout << "  No loops found." << std::endl;
+    return;
+  }
+
+  std::cout << "Total Loops Found: " << AllLoops.size() << std::endl;
+
+  // 1. 按层级分组循环
+  std::map<int, std::vector<Loop*>> loopsByLevel;
+  int maxLevel = 0;
+  for (const auto& loop_ptr : AllLoops) {
+      if (loop_ptr->getLoopLevel() != -1) { // 确保层级已计算
+          loopsByLevel[loop_ptr->getLoopLevel()].push_back(loop_ptr.get());
+          if (loop_ptr->getLoopLevel() > maxLevel) {
+              maxLevel = loop_ptr->getLoopLevel();
+          }
+      }
+  }
+
+  // 2. 打印循环层次结构
+  std::cout << "\n--- Loop Hierarchy ---" << std::endl;
+  for (int level = 0; level <= maxLevel; ++level) {
+      if (loopsByLevel.count(level)) {
+          std::cout << "Level " << level << " Loops:" << std::endl;
+          for (Loop* loop : loopsByLevel[level]) {
+              std::string indent(level * 2, ' '); // 根据层级缩进
+              std::cout << indent << "- Loop Header: " << loop->getName() << std::endl;
+              std::cout << indent << "  Blocks: ";
+              printBBSet("", loop->getBlocks());
+              std::cout << std::endl;
+
+              std::cout << indent << "  Exit Blocks: ";
+              printBBSet("", loop->getExitBlocks());
+              std::cout << std::endl;
+
+              std::cout << indent << "  Pre-Header: " << (loop->getPreHeader() ? loop->getPreHeader()->getName() : "None") << std::endl;
+              std::cout << indent << "  Parent Loop: " << (loop->getParentLoop() ? loop->getParentLoop()->getName() : "None (Outermost)") << std::endl;
+              std::cout << indent << "  Nested Loops: ";
+              printLoopVector("", loop->getNestedLoops());
+              std::cout << std::endl;
+          }
+      }
+  }
+
+  // 3. 打印最外层/最内层循环摘要
+  std::cout << "\n--- Loop Summary ---" << std::endl;
+  std::cout << "Outermost Loops: ";
+  printLoopVector("", getOutermostLoops());
+  std::cout << std::endl;
+
+  std::cout << "Innermost Loops: ";
+  printLoopVector("", getInnermostLoops());
+  std::cout << std::endl;
+
+  std::cout << "-----------------------------------------------" << std::endl;
+}
+
+bool LoopAnalysisPass::runOnFunction(Function *F, AnalysisManager &AM) {
+  if (F->getBasicBlocks().empty()) {
+    CurrentResult = std::make_unique<LoopAnalysisResult>(F);
+    return false; // 空函数，没有循环
+  }
+
+  if (DEBUG)
+    std::cout << "Running LoopAnalysisPass on function: " << F->getName() << std::endl;
+
+  // 获取支配树分析结果
+  // 这是循环分析的关键依赖
+  DominatorTree *DT = AM.getAnalysisResult<DominatorTree, DominatorTreeAnalysisPass>(F);
+  if (!DT) {
+    // 无法获取支配树，无法进行循环分析
+    std::cerr << "Error: DominatorTreeAnalysisResult not available for function " << F->getName() << std::endl;
+    CurrentResult = std::make_unique<LoopAnalysisResult>(F);
+    return false;
+  }
+
+  // 获取别名分析结果 - 用于循环内存访问分析
+  AliasAnalysisResult *aliasAnalysis = AM.getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(F);
+  if (DEBUG && aliasAnalysis) {
+    std::cout << "Loop Analysis: Using alias analysis results for enhanced memory pattern detection" << std::endl;
+  }
+
+  // 获取副作用分析结果 - 用于循环纯度分析
+  SideEffectAnalysisResult *sideEffectAnalysis = AM.getAnalysisResult<SideEffectAnalysisResult, SysYSideEffectAnalysisPass>();
+  if (DEBUG && sideEffectAnalysis) {
+    std::cout << "Loop Analysis: Using side effect analysis results for loop purity detection" << std::endl;
+  }
+
+  CurrentResult = std::make_unique<LoopAnalysisResult>(F);
+  bool changed = false; // 循环分析本身不修改IR，所以通常返回false
+
+  // 步骤 1: 识别回边和对应的自然循环
+  // 回边 (N -> D) 定义：D 支配 N
+  std::vector<std::pair<BasicBlock *, BasicBlock *>> backEdges;
+  for (auto &BB : F->getBasicBlocks()) {
+    auto Block = BB.get();
+    for (BasicBlock *Succ : Block->getSuccessors()) {
+      if (DT->getDominators(Block) && DT->getDominators(Block)->count(Succ)) {
+        // Succ 支配 Block，所以 (Block -> Succ) 是一条回边
+        backEdges.push_back({Block, Succ});
+        if (DEBUG)
+          std::cout << "Found back edge: " << Block->getName() << " -> " << Succ->getName() << std::endl;
+      }
+    }
+  }
+  
+  if (DEBUG)
+    std::cout << "Total back edges found: " << backEdges.size() << std::endl;
+
+  // 步骤 2: 为每条回边构建自然循环
+  std::map<BasicBlock*, std::unique_ptr<Loop>> loopMap; // 按循环头分组
+  
+  for (auto &edge : backEdges) {
+    BasicBlock *N = edge.first;  // 回边的尾部
+    BasicBlock *D = edge.second; // 回边的头部 (循环头)
+
+    // 检查是否已经为此循环头创建了循环
+    if (loopMap.find(D) == loopMap.end()) {
+      // 创建新的 Loop 对象
+      loopMap[D] = std::make_unique<Loop>(D);
+    }
+    
+    Loop* currentLoop = loopMap[D].get();
+
+    // 收集此回边对应的循环体块：从 N 逆向遍历到 D
+    std::set<BasicBlock *> loopBlocks; // 临时存储循环块
+    std::queue<BasicBlock *> q;
+
+    // 循环头总是循环体的一部分
+    loopBlocks.insert(D);
+    
+    // 如果回边的尾部不是循环头本身，则将其加入队列进行遍历
+    if (N != D) {
+      q.push(N);
+      loopBlocks.insert(N);
+    }
+
+    while (!q.empty()) {
+      BasicBlock *current = q.front();
+      q.pop();
+
+      for (BasicBlock *pred : current->getPredecessors()) {
+        // 如果前驱还没有被访问过，则将其加入循环体并继续遍历
+        if (loopBlocks.find(pred) == loopBlocks.end()) {
+          loopBlocks.insert(pred);
+          q.push(pred);
+        }
+      }
+    }
+
+    // 将收集到的块添加到 Loop 对象中（合并所有回边的结果）
+    for (BasicBlock *loopBB : loopBlocks) {
+      currentLoop->addBlock(loopBB);
+    }
+  }
+
+  // 处理每个合并后的循环
+  for (auto &[header, currentLoop] : loopMap) {
+    const auto &loopBlocks = currentLoop->getBlocks();
+
+    // 步骤 3: 识别循环出口块 (Exit Blocks)
+    for (BasicBlock *loopBB : loopBlocks) {
+      for (BasicBlock *succ : loopBB->getSuccessors()) {
+        if (loopBlocks.find(succ) == loopBlocks.end()) {
+          // 如果后继不在循环体内，则 loopBB 是一个出口块
+          currentLoop->addExitBlock(loopBB);
+        }
+      }
+    }
+
+    // 步骤 4: 识别循环前置块 (Pre-Header)
+    BasicBlock *candidatePreHeader = nullptr;
+    int externalPredecessorCount = 0;
+    for (BasicBlock *predOfHeader : header->getPredecessors()) {
+      // 使用 currentLoop->contains() 来检查前驱是否在循环体内
+      if (!currentLoop->contains(predOfHeader)) {
+        // 如果前驱不在循环体内，则是一个外部前驱
+        externalPredecessorCount++;
+        candidatePreHeader = predOfHeader;
+      }
+    }
+
+    if (externalPredecessorCount == 1) {
+      currentLoop->setPreHeader(candidatePreHeader);
+    }
+    CurrentResult->addLoop(std::move(currentLoop));
+  }
+
+  // 步骤 5: 处理嵌套循环 (确定父子关系和层级)
+  const auto &allLoops = CurrentResult->getAllLoops();
+
+  // 1. 首先，清除所有循环已设置的父子关系和嵌套子循环列表，确保重新计算
+  for (const auto &loop_ptr : allLoops) {
+      loop_ptr->setParentLoop(nullptr); // 清除父指针
+      loop_ptr->clearNestedLoops();     // 清除子循环列表
+      loop_ptr->setLoopLevel(-1);       // 重置循环层级
+  }
+
+  // 2. 遍历所有循环，为每个循环找到其直接父循环并建立关系
+  for (const auto &innerLoop_ptr : allLoops) {
+    Loop *innerLoop = innerLoop_ptr.get();
+    Loop *immediateParent = nullptr; // 用于存储当前 innerLoop 的最近父循环
+
+    for (const auto &outerLoop_ptr : allLoops) {
+      Loop *outerLoop = outerLoop_ptr.get();
+
+      // 一个循环不能是它自己的父循环
+      if (outerLoop == innerLoop) {
+        continue;
+      }
+
+      // 检查 outerLoop 是否包含 innerLoop 的所有条件：
+      // Condition 1: outerLoop 的头支配 innerLoop 的头
+      if (!(DT->getDominators(innerLoop->getHeader()) &&
+            DT->getDominators(innerLoop->getHeader())->count(outerLoop->getHeader()))) {
+        continue; // outerLoop 不支配 innerLoop 的头，因此不是一个外层循环
+      }
+
+      // Condition 2: innerLoop 的所有基本块都在 outerLoop 的基本块集合中
+      bool allInnerBlocksInOuter = true;
+      for (BasicBlock *innerBB : innerLoop->getBlocks()) {
+        if (!outerLoop->contains(innerBB)) { //
+          allInnerBlocksInOuter = false;
+          break;
+        }
+      }
+      if (!allInnerBlocksInOuter) {
+        continue; // outerLoop 不包含 innerLoop 的所有块
+      }
+
+      // 到此为止，outerLoop 已经被确认为 innerLoop 的一个“候选父循环”（即它包含了 innerLoop）
+
+      if (immediateParent == nullptr) {
+        // 这是找到的第一个候选父循环
+        immediateParent = outerLoop;
+      } else {
+        // 已经有了一个 immediateParent，需要判断哪个是更“紧密”的父循环
+        // 更紧密的父循环是那个包含另一个候选父循环的。
+        // 如果当前的 immediateParent 包含了 outerLoop 的头，那么 outerLoop 是更深的循环（更接近 innerLoop）
+        if (immediateParent->contains(outerLoop->getHeader())) { //
+          immediateParent = outerLoop; // outerLoop 是更紧密的父循环
+        }
+        // 否则（outerLoop 包含了 immediateParent 的头），说明 immediateParent 更紧密，保持不变
+        // 或者它们互不包含（不应该发生，因为它们都包含了 innerLoop），也保持 immediateParent
+      }
+    }
+
+    // 设置 innerLoop 的直接父循环，并添加到父循环的嵌套列表中
+    if (immediateParent) {
+      innerLoop->setParentLoop(immediateParent);
+      immediateParent->addNestedLoop(innerLoop); 
+    }
+  }
+
+  // 3. 计算循环层级 (Level)
+  std::queue<Loop *> q_level;
+
+  // 查找所有最外层循环（没有父循环的），设置其层级为0，并加入队列
+  for (const auto &loop_ptr : allLoops) {
+    if (loop_ptr->isOutermost()) {
+      loop_ptr->setLoopLevel(0);
+      q_level.push(loop_ptr.get());
+    }
+  }
+
+  // 使用 BFS 遍历循环树，计算所有嵌套循环的层级
+  while (!q_level.empty()) {
+    Loop *current = q_level.front();
+    q_level.pop();
+
+    for (Loop *nestedLoop : current->getNestedLoops()) {
+      nestedLoop->setLoopLevel(current->getLoopLevel() + 1);
+      q_level.push(nestedLoop);
+    }
+  }
+
+  if (DEBUG) {
+    std::cout << "Loop Analysis completed for function: " << F->getName() << std::endl;
+    std::cout << "Total loops found: " << CurrentResult->getLoopCount() << std::endl;
+    std::cout << "Max loop depth: " << CurrentResult->getMaxLoopDepth() << std::endl;
+    std::cout << "Innermost loops: " << CurrentResult->getInnermostLoops().size() << std::endl;
+    std::cout << "Outermost loops: " << CurrentResult->getOutermostLoops().size() << std::endl;
+    
+    // 打印各深度的循环分布
+    for (int depth = 1; depth <= CurrentResult->getMaxLoopDepth(); ++depth) {
+      int count = CurrentResult->getLoopCountAtDepth(depth);
+      if (count > 0) {
+        std::cout << "Loops at depth " << depth << ": " << count << std::endl;
+      }
+    }
+    
+    // 输出缓存统计
+    auto cacheStats = CurrentResult->getCacheStats();
+    std::cout << "Cache statistics - Total cached queries: " << cacheStats.totalCachedQueries << std::endl;
+  }
+
+  return changed;
+}
+
+// ========== Loop 类的新增方法实现 ==========
+
+bool Loop::mayHaveSideEffects(SideEffectAnalysisResult* sideEffectAnalysis) const {
+  if (!sideEffectAnalysis) return true; // 保守假设
+  
+  for (BasicBlock* bb : LoopBlocks) {
+    for (auto& inst : bb->getInstructions()) {
+      if (sideEffectAnalysis->hasSideEffect(inst.get())) {
+        return true;
+      }
+    }
+  }
+  return false;
+}
+
+bool Loop::accessesGlobalMemory(AliasAnalysisResult* aliasAnalysis) const {
+  if (!aliasAnalysis) return true; // 保守假设
+  
+  for (BasicBlock* bb : LoopBlocks) {
+    for (auto& inst : bb->getInstructions()) {
+      if (auto* loadInst = dynamic_cast<LoadInst*>(inst.get())) {
+        if (!aliasAnalysis->isLocalArray(loadInst->getPointer())) {
+          return true;
+        }
+      } else if (auto* storeInst = dynamic_cast<StoreInst*>(inst.get())) {
+        if (!aliasAnalysis->isLocalArray(storeInst->getPointer())) {
+          return true;
+        }
+      }
+    }
+  }
+  return false;
+}
+
+bool Loop::hasMemoryAliasConflicts(AliasAnalysisResult* aliasAnalysis) const {
+  if (!aliasAnalysis) return true; // 保守假设
+  
+  std::vector<Value*> memoryAccesses;
+  
+  // 收集所有内存访问
+  for (BasicBlock* bb : LoopBlocks) {
+    for (auto& inst : bb->getInstructions()) {
+      if (auto* loadInst = dynamic_cast<LoadInst*>(inst.get())) {
+        memoryAccesses.push_back(loadInst->getPointer());
+      } else if (auto* storeInst = dynamic_cast<StoreInst*>(inst.get())) {
+        memoryAccesses.push_back(storeInst->getPointer());
+      }
+    }
+  }
+  
+  // 检查两两之间是否有别名
+  for (size_t i = 0; i < memoryAccesses.size(); ++i) {
+    for (size_t j = i + 1; j < memoryAccesses.size(); ++j) {
+      auto aliasType = aliasAnalysis->queryAlias(memoryAccesses[i], memoryAccesses[j]);
+      if (aliasType == AliasType::SELF_ALIAS || aliasType == AliasType::POSSIBLE_ALIAS) {
+        return true;
+      }
+    }
+  }
+  
+  return false;
+}
+
+} // namespace sysy

src/midend/Pass/Analysis/LoopCharacteristics.cpp

@@ -0,0 +1,813 @@
+#include "LoopCharacteristics.h"
+#include "Dom.h"
+#include "Loop.h"
+#include "Liveness.h"
+#include "AliasAnalysis.h"
+#include "SideEffectAnalysis.h"
+#include <iostream>
+#include <cmath>
+
+// 使用全局调试开关
+extern int DEBUG;
+
+namespace sysy {
+
+// 定义 Pass 的唯一 ID
+void *LoopCharacteristicsPass::ID = (void *)&LoopCharacteristicsPass::ID;
+
+void LoopCharacteristicsResult::print() const {
+  if (!DEBUG) return;
+
+  std::cout << "\n--- Loop Characteristics Analysis Results for Function: " 
+            << AssociatedFunction->getName() << " ---" << std::endl;
+
+  if (CharacteristicsMap.empty()) {
+    std::cout << "  No loop characteristics found." << std::endl;
+    return;
+  }
+
+  // 打印统计信息
+  auto stats = getOptimizationStats();
+  std::cout << "\n=== Basic Loop Characteristics Statistics ===" << std::endl;
+  std::cout << "Total Loops: " << stats.totalLoops << std::endl;
+  std::cout << "Counting Loops: " << stats.countingLoops << std::endl;
+  std::cout << "Unrolling Candidates: " << stats.unrollingCandidates << std::endl;
+  std::cout << "Pure Loops: " << stats.pureLoops << std::endl;
+  std::cout << "Local Memory Only Loops: " << stats.localMemoryOnlyLoops << std::endl;
+  std::cout << "No Alias Conflict Loops: " << stats.noAliasConflictLoops << std::endl;
+  std::cout << "Avg Instructions per Loop: " << stats.avgInstructionCount << std::endl;
+  std::cout << "Avg Compute/Memory Ratio: " << stats.avgComputeMemoryRatio << std::endl;
+
+  // 按热度排序并打印循环特征
+  auto loopsByHotness = getLoopsByHotness();
+  std::cout << "\n=== Loop Characteristics (by hotness) ===" << std::endl;
+  
+  for (auto* loop : loopsByHotness) {
+    auto* chars = getCharacteristics(loop);
+    if (!chars) continue;
+    
+    std::cout << "\n--- Loop: " << loop->getName() << " (Hotness: " 
+              << loop->getLoopHotness() << ") ---" << std::endl;
+    std::cout << "  Level: " << loop->getLoopLevel() << std::endl;
+    std::cout << "  Blocks: " << loop->getLoopSize() << std::endl;
+    std::cout << "  Instructions: " << chars->instructionCount << std::endl;
+    std::cout << "  Memory Operations: " << chars->memoryOperationCount << std::endl;
+    std::cout << "  Compute/Memory Ratio: " << chars->computeToMemoryRatio << std::endl;
+    
+    // 循环形式
+    std::cout << "  Form: ";
+    if (chars->isCountingLoop) std::cout << "Counting ";
+    if (chars->isSimpleForLoop) std::cout << "SimpleFor ";
+    if (chars->isInnermost) std::cout << "Innermost ";
+    if (chars->hasComplexControlFlow) std::cout << "Complex ";
+    if (chars->isPure) std::cout << "Pure ";
+    if (chars->accessesOnlyLocalMemory) std::cout << "LocalMemOnly ";
+    if (chars->hasNoMemoryAliasConflicts) std::cout << "NoAliasConflicts ";
+    std::cout << std::endl;
+    
+    // 边界信息
+    if (chars->staticTripCount.has_value()) {
+      std::cout << "  Static Trip Count: " << *chars->staticTripCount << std::endl;
+    }
+    if (chars->hasKnownBounds) {
+      std::cout << "  Has Known Bounds: Yes" << std::endl;
+    }
+    
+    // 优化机会
+    std::cout << "  Optimization Opportunities: ";
+    if (chars->benefitsFromUnrolling) 
+      std::cout << "Unroll(factor=" << chars->suggestedUnrollFactor << ") ";
+    std::cout << std::endl;
+    
+    // 归纳变量
+    if (!chars->InductionVars.empty()) {
+      std::cout << "  Induction Vars: " << chars->InductionVars.size() << std::endl;
+    }
+    
+    // 循环不变量
+    if (!chars->loopInvariants.empty()) {
+      std::cout << "  Loop Invariants: " << chars->loopInvariants.size() << std::endl;
+    }
+    if (!chars->invariantInsts.empty()) {
+      std::cout << "  Hoistable Instructions: " << chars->invariantInsts.size() << std::endl;
+    }
+  }
+  
+  std::cout << "-----------------------------------------------" << std::endl;
+}
+
+bool LoopCharacteristicsPass::runOnFunction(Function *F, AnalysisManager &AM) {
+  if (F->getBasicBlocks().empty()) {
+    CurrentResult = std::make_unique<LoopCharacteristicsResult>(F);
+    return false; // 空函数
+  }
+
+  if (DEBUG)
+    std::cout << "Running LoopCharacteristicsPass on function: " << F->getName() << std::endl;
+
+  // 获取并缓存所有需要的分析结果
+  loopAnalysis = AM.getAnalysisResult<LoopAnalysisResult, LoopAnalysisPass>(F);
+  if (!loopAnalysis) {
+    std::cerr << "Error: LoopAnalysisResult not available for function " << F->getName() << std::endl;
+    CurrentResult = std::make_unique<LoopCharacteristicsResult>(F);
+    return false;
+  }
+
+  // 如果没有循环，直接返回
+  if (!loopAnalysis->hasLoops()) {
+    CurrentResult = std::make_unique<LoopCharacteristicsResult>(F);
+    return false;
+  }
+
+  // 获取别名分析和副作用分析结果并缓存
+  aliasAnalysis = AM.getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(F);
+  sideEffectAnalysis = AM.getAnalysisResult<SideEffectAnalysisResult, SysYSideEffectAnalysisPass>();
+
+  if (DEBUG) {
+    if (aliasAnalysis) std::cout << "LoopCharacteristics: Using alias analysis results" << std::endl;
+    if (sideEffectAnalysis) std::cout << "LoopCharacteristics: Using side effect analysis results" << std::endl;
+  }
+
+  CurrentResult = std::make_unique<LoopCharacteristicsResult>(F);
+
+  // 分析每个循环的特征 - 现在不需要传递分析结果参数
+  for (const auto& loop_ptr : loopAnalysis->getAllLoops()) {
+    Loop* loop = loop_ptr.get();
+    auto characteristics = std::make_unique<LoopCharacteristics>(loop);
+    
+    // 执行各种特征分析，使用缓存的分析结果
+    analyzeLoop(loop, characteristics.get());
+    
+    // 添加到结果中
+    CurrentResult->addLoopCharacteristics(std::move(characteristics));
+  }
+
+  if (DEBUG) {
+    std::cout << "LoopCharacteristicsPass completed for function: " << F->getName() << std::endl;
+    auto stats = CurrentResult->getOptimizationStats();
+    std::cout << "Analyzed " << stats.totalLoops << " loops, found " 
+              << stats.countingLoops << " counting loops, " 
+              << stats.unrollingCandidates << " unroll candidates" << std::endl;
+  }
+
+  return false; // 特征分析不修改IR
+}
+
+void LoopCharacteristicsPass::analyzeLoop(Loop* loop, LoopCharacteristics* characteristics) {
+  if (DEBUG)
+    std::cout << "  Analyzing basic characteristics of loop: " << loop->getName() << std::endl;
+
+  // 按顺序执行基础分析 - 现在使用缓存的分析结果
+  computePerformanceMetrics(loop, characteristics);
+  analyzeLoopForm(loop, characteristics);
+  analyzePurityAndSideEffects(loop, characteristics);
+  identifyBasicInductionVariables(loop, characteristics);
+  identifyBasicLoopInvariants(loop, characteristics);
+  analyzeBasicLoopBounds(loop, characteristics);
+  analyzeBasicMemoryAccessPatterns(loop, characteristics);
+  evaluateBasicOptimizationOpportunities(loop, characteristics);
+}
+
+void LoopCharacteristicsPass::computePerformanceMetrics(Loop* loop, LoopCharacteristics* characteristics) {
+  size_t totalInsts = 0;
+  size_t memoryOps = 0;
+  size_t arithmeticOps = 0;
+
+  // 遍历循环中的所有指令
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      totalInsts++;
+      
+      // 分类指令类型
+      if (dynamic_cast<LoadInst*>(inst.get()) || dynamic_cast<StoreInst*>(inst.get())) {
+        memoryOps++;
+      } else if (dynamic_cast<BinaryInst*>(inst.get())) {
+        // 检查是否为算术运算
+        auto* binInst = dynamic_cast<BinaryInst*>(inst.get());
+        // 简化：假设所有二元运算都是算术运算
+        arithmeticOps++;
+      }
+    }
+  }
+
+  characteristics->instructionCount = totalInsts;
+  characteristics->memoryOperationCount = memoryOps;
+  characteristics->arithmeticOperationCount = arithmeticOps;
+  
+  // 计算计算与内存操作比率
+  if (memoryOps > 0) {
+    characteristics->computeToMemoryRatio = static_cast<double>(arithmeticOps) / memoryOps;
+  } else {
+    characteristics->computeToMemoryRatio = arithmeticOps; // 纯计算循环
+  }
+}
+
+void LoopCharacteristicsPass::analyzeLoopForm(Loop* loop, LoopCharacteristics* characteristics) {
+  // 基本形式判断
+  characteristics->isInnermost = loop->isInnermost();
+  
+  // 检查是否为简单循环 (只有一个回边)
+  bool isSimple = loop->isSimpleLoop();
+  characteristics->isSimpleForLoop = isSimple;
+  
+  // 检查复杂控制流 (多个出口表示可能有break/continue)
+  auto exitingBlocks = loop->getExitingBlocks();
+  characteristics->hasComplexControlFlow = exitingBlocks.size() > 1;
+  
+  // 初步判断是否为计数循环 (需要更复杂的分析)
+  // 简化版本：如果是简单循环且是最内层，很可能是计数循环
+  characteristics->isCountingLoop = isSimple && loop->isInnermost() && exitingBlocks.size() == 1;
+}
+
+void LoopCharacteristicsPass::analyzePurityAndSideEffects(Loop* loop, LoopCharacteristics* characteristics) {
+  if (!sideEffectAnalysis) {
+    // 没有副作用分析结果，保守处理
+    characteristics->isPure = false;
+    return;
+  }
+  
+  // 检查循环是否有副作用
+  characteristics->isPure = !loop->mayHaveSideEffects(sideEffectAnalysis);
+  
+  if (DEBUG && characteristics->isPure) {
+    std::cout << "    Loop " << loop->getName() << " is identified as PURE (no side effects)" << std::endl;
+  }
+}
+
+void LoopCharacteristicsPass::analyzeBasicMemoryAccessPatterns(Loop* loop, LoopCharacteristics* characteristics) {
+  if (!aliasAnalysis) {
+    // 没有别名分析结果，保守处理
+    characteristics->accessesOnlyLocalMemory = false;
+    characteristics->hasNoMemoryAliasConflicts = false;
+    return;
+  }
+  
+  // 检查是否只访问局部内存
+  characteristics->accessesOnlyLocalMemory = !loop->accessesGlobalMemory(aliasAnalysis);
+  
+  // 检查是否有内存别名冲突
+  characteristics->hasNoMemoryAliasConflicts = !loop->hasMemoryAliasConflicts(aliasAnalysis);
+  
+  if (DEBUG) {
+    if (characteristics->accessesOnlyLocalMemory) {
+      std::cout << "    Loop " << loop->getName() << " accesses ONLY LOCAL MEMORY" << std::endl;
+    }
+    if (characteristics->hasNoMemoryAliasConflicts) {
+      std::cout << "    Loop " << loop->getName() << " has NO MEMORY ALIAS CONFLICTS" << std::endl;
+    }
+  }
+  
+  // 分析基础的内存访问模式
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      if (auto* loadInst = dynamic_cast<LoadInst*>(inst.get())) {
+        Value* ptr = loadInst->getPointer();
+        
+        auto& pattern = characteristics->memoryPatterns[ptr];
+        pattern.loadInsts.push_back(loadInst);
+        pattern.isArrayParameter = aliasAnalysis->isFunctionParameter(ptr);
+        pattern.isGlobalArray = aliasAnalysis->isGlobalArray(ptr);
+        pattern.hasConstantIndices = aliasAnalysis->hasConstantAccess(ptr);
+        
+      } else if (auto* storeInst = dynamic_cast<StoreInst*>(inst.get())) {
+        Value* ptr = storeInst->getPointer();
+        
+        auto& pattern = characteristics->memoryPatterns[ptr];
+        pattern.storeInsts.push_back(storeInst);
+        pattern.isArrayParameter = aliasAnalysis->isFunctionParameter(ptr);
+        pattern.isGlobalArray = aliasAnalysis->isGlobalArray(ptr);
+        pattern.hasConstantIndices = aliasAnalysis->hasConstantAccess(ptr);
+      }
+    }
+  }
+}
+
+bool LoopCharacteristicsPass::isBasicInductionVariable(Value* val, Loop* loop) {
+  // 简化的基础归纳变量检测
+  auto* phiInst = dynamic_cast<PhiInst*>(val);
+  if (!phiInst) return false;
+  
+  // 检查phi指令是否在循环头
+  if (phiInst->getParent() != loop->getHeader()) return false;
+  
+  // 检查是否有来自循环内的更新
+  for (auto& [incomingBB, incomingVal] : phiInst->getIncomingValues()) {
+    if (loop->contains(incomingBB)) {
+      return true; // 简化：有来自循环内的值就认为是基础归纳变量
+    }
+  }
+  
+  return false;
+}
+
+
+void LoopCharacteristicsPass::identifyBasicInductionVariables(
+    Loop* loop, LoopCharacteristics* characteristics) {
+  BasicBlock* header = loop->getHeader();
+  std::vector<std::unique_ptr<InductionVarInfo>> ivs;
+
+  if (DEBUG) {
+    std::cout << "    === Identifying Induction Variables for Loop: " << loop->getName() << " ===" << std::endl;
+    std::cout << "    Loop header: " << header->getName() << std::endl;
+    std::cout << "    Loop blocks: ";
+    for (auto* bb : loop->getBlocks()) {
+      std::cout << bb->getName() << " ";
+    }
+    std::cout << std::endl;
+  }
+
+  // 1. 识别所有BIV
+  for (auto& inst : header->getInstructions()) {
+    auto* phi = dynamic_cast<PhiInst*>(inst.get());
+    if (!phi) continue;
+    if (isBasicInductionVariable(phi, loop)) {
+      ivs.push_back(InductionVarInfo::createBasicBIV(phi, Instruction::Kind::kPhi, phi));
+      if (DEBUG) {
+        std::cout << "    [BIV] Found basic induction variable: " << phi->getName() << std::endl;
+        std::cout << "          Incoming values: ";
+        for (auto& [incomingBB, incomingVal] : phi->getIncomingValues()) {
+          std::cout << "{" << incomingBB->getName() << ": " << incomingVal->getName() << "} ";
+        }
+        std::cout << std::endl;
+      }
+    }
+  }
+
+  if (DEBUG) {
+    std::cout << "    Found " << ivs.size() << " basic induction variables" << std::endl;
+  }
+
+  // 2. 递归识别所有派生DIV
+  std::set<Value*> visited;
+  size_t initialSize = ivs.size();
+  
+  // 保存初始的BIV列表，避免在遍历过程中修改向量导致迭代器失效
+  std::vector<InductionVarInfo*> bivList;
+  for (size_t i = 0; i < initialSize; ++i) {
+    if (ivs[i] && ivs[i]->ivkind == IVKind::kBasic) {
+      bivList.push_back(ivs[i].get());
+    }
+  }
+  
+  for (auto* biv : bivList) {
+    if (DEBUG) {
+      if (biv && biv->div) {
+        std::cout << "    Searching for derived IVs from BIV: " << biv->div->getName() << std::endl;
+      } else {
+        std::cout << "    ERROR: Invalid BIV pointer or div field is null" << std::endl;
+        continue;
+      }
+    }
+    findDerivedInductionVars(biv->div, biv->base, loop, ivs, visited);
+  }
+
+  if (DEBUG) {
+    size_t derivedCount = ivs.size() - initialSize;
+    std::cout << "    Found " << derivedCount << " derived induction variables" << std::endl;
+    
+    // 打印所有归纳变量的详细信息
+    std::cout << "    === Final Induction Variables Summary ===" << std::endl;
+    for (size_t i = 0; i < ivs.size(); ++i) {
+      const auto& iv = ivs[i];
+      std::cout << "    [" << i << "] " << iv->div->getName() 
+                << " (kind: " << (iv->ivkind == IVKind::kBasic ? "Basic" : 
+                               iv->ivkind == IVKind::kLinear ? "Linear" : "Complex") << ")" << std::endl;
+      std::cout << "        Operation: " << static_cast<int>(iv->Instkind) << std::endl;
+      if (iv->base) {
+        std::cout << "        Base: " << iv->base->getName() << std::endl;
+      }
+      if (iv->Multibase.first || iv->Multibase.second) {
+        std::cout << "        Multi-base: ";
+        if (iv->Multibase.first) std::cout << iv->Multibase.first->getName() << " ";
+        if (iv->Multibase.second) std::cout << iv->Multibase.second->getName() << " ";
+        std::cout << std::endl;
+      }
+      std::cout << "        Factor: " << iv->factor << ", Offset: " << iv->offset << std::endl;
+      std::cout << "        Valid: " << (iv->valid ? "Yes" : "No") << std::endl;
+    }
+    std::cout << "    =============================================" << std::endl;
+  }
+
+  characteristics->InductionVars = std::move(ivs);
+}
+
+
+struct LinearExpr {
+  // 表达为: a * base1 + b * base2 + offset
+  Value* base1 = nullptr;
+  Value* base2 = nullptr;
+  int factor1 = 0;
+  int factor2 = 0;
+  int offset = 0;
+  bool valid = false;
+  bool isSimple = false; // 仅一个BIV时true
+};
+
+static LinearExpr analyzeLinearExpr(Value* val, Loop* loop, std::vector<std::unique_ptr<InductionVarInfo>>& ivs) {
+  // 递归归约val为线性表达式
+  // 只支持单/双BIV线性组合
+  // 见下方详细实现
+  // ----------
+  if (DEBUG >= 2) {  // 更详细的调试级别
+    if (auto* inst = dynamic_cast<Instruction*>(val)) {
+      std::cout << "        Analyzing linear expression for: " << val->getName() 
+                << " (kind: " << static_cast<int>(inst->getKind()) << ")" << std::endl;
+    } else {
+      std::cout << "        Analyzing linear expression for value: " << val->getName() << std::endl;
+    }
+  }
+  
+  // 基本变量：常数
+  if (auto* cint = dynamic_cast<ConstantInteger*>(val)) {
+    if (DEBUG >= 2) {
+      std::cout << "        -> Constant: " << cint->getInt() << std::endl;
+    }
+    return {nullptr, nullptr, 0, 0, cint->getInt(), true, false};
+  }
+  
+  // 基本变量：BIV或派生IV
+  for (auto& iv : ivs) {
+    if (iv->div == val) {
+      if (iv->ivkind == IVKind::kBasic ||
+          iv->ivkind == IVKind::kLinear) {
+        if (DEBUG >= 2) {
+          std::cout << "        -> Found " << (iv->ivkind == IVKind::kBasic ? "Basic" : "Linear") 
+                    << " IV with base: " << (iv->base ? iv->base->getName() : "null") 
+                    << ", factor: " << iv->factor << ", offset: " << iv->offset << std::endl;
+        }
+        return {iv->base, nullptr, iv->factor, 0, iv->offset, true, true};
+      }
+      // 复杂归纳变量
+      if (iv->ivkind == IVKind::kCmplx) {
+        if (DEBUG >= 2) {
+          std::cout << "        -> Found Complex IV with multi-base" << std::endl;
+        }
+        return {iv->Multibase.first, iv->Multibase.second, 1, 1, 0, true, false};
+      }
+    }
+  }
+  
+  // 一元负号
+  if (auto* inst = dynamic_cast<Instruction*>(val)) {
+    auto kind = inst->getKind();
+    if (kind == Instruction::Kind::kNeg) {
+      if (DEBUG >= 2) {
+        std::cout << "        -> Analyzing negation" << std::endl;
+      }
+      auto expr = analyzeLinearExpr(inst->getOperand(0), loop, ivs);
+      if (!expr.valid) return expr;
+      expr.factor1 = -expr.factor1;
+      expr.factor2 = -expr.factor2;
+      expr.offset = -expr.offset;
+      expr.isSimple = (expr.base2 == nullptr);
+      if (DEBUG >= 2) {
+        std::cout << "        -> Negation result: valid=" << expr.valid << ", simple=" << expr.isSimple << std::endl;
+      }
+      return expr;
+    }
+    
+    // 二元加减乘
+    if (kind == Instruction::Kind::kAdd || kind == Instruction::Kind::kSub) {
+      if (DEBUG >= 2) {
+        std::cout << "        -> Analyzing " << (kind == Instruction::Kind::kAdd ? "addition" : "subtraction") << std::endl;
+      }
+      auto expr0 = analyzeLinearExpr(inst->getOperand(0), loop, ivs);
+      auto expr1 = analyzeLinearExpr(inst->getOperand(1), loop, ivs);
+      if (!expr0.valid || !expr1.valid) {
+        if (DEBUG >= 2) {
+          std::cout << "        -> Failed: operand not linear (expr0.valid=" << expr0.valid << ", expr1.valid=" << expr1.valid << ")" << std::endl;
+        }
+        return {nullptr, nullptr, 0, 0, 0, false, false};
+      }
+      
+      // 合并：若BIV相同或有一个是常数
+      // 单BIV+常数
+      if (expr0.base1 && !expr1.base1 && !expr1.base2) {
+        int sign = (kind == Instruction::Kind::kAdd ? 1 : -1);
+        if (DEBUG >= 2) {
+          std::cout << "        -> Single BIV + constant pattern" << std::endl;
+        }
+        return {expr0.base1, nullptr, expr0.factor1, 0, expr0.offset + sign * expr1.offset, true, expr0.isSimple};
+      }
+      if (!expr0.base1 && !expr0.base2 && expr1.base1) {
+        int sign = (kind == Instruction::Kind::kAdd ? 1 : -1);
+        int f = sign * expr1.factor1;
+        int off = expr0.offset + sign * expr1.offset;
+        if (DEBUG >= 2) {
+          std::cout << "        -> Constant + single BIV pattern" << std::endl;
+        }
+        return {expr1.base1, nullptr, f, 0, off, true, expr1.isSimple};
+      }
+      
+      // 双BIV线性组合
+      if (expr0.base1 && expr1.base1 && expr0.base1 != expr1.base1 && !expr0.base2 && !expr1.base2) {
+        int sign = (kind == Instruction::Kind::kAdd ? 1 : -1);
+        Value* base1 = expr0.base1;
+        Value* base2 = expr1.base1;
+        int f1 = expr0.factor1;
+        int f2 = sign * expr1.factor1;
+        int off = expr0.offset + sign * expr1.offset;
+        if (DEBUG >= 2) {
+          std::cout << "        -> Double BIV linear combination" << std::endl;
+        }
+        return {base1, base2, f1, f2, off, true, false};
+      }
+      
+      // 同BIV合并
+      if (expr0.base1 && expr1.base1 && expr0.base1 == expr1.base1 && !expr0.base2 && !expr1.base2) {
+        int sign = (kind == Instruction::Kind::kAdd ? 1 : -1);
+        int f = expr0.factor1 + sign * expr1.factor1;
+        int off = expr0.offset + sign * expr1.offset;
+        if (DEBUG >= 2) {
+          std::cout << "        -> Same BIV combination" << std::endl;
+        }
+        return {expr0.base1, nullptr, f, 0, off, true, true};
+      }
+    }
+    
+    // 乘法：BIV*const 或 const*BIV
+    if (kind == Instruction::Kind::kMul) {
+      if (DEBUG >= 2) {
+        std::cout << "        -> Analyzing multiplication" << std::endl;
+      }
+      auto expr0 = analyzeLinearExpr(inst->getOperand(0), loop, ivs);
+      auto expr1 = analyzeLinearExpr(inst->getOperand(1), loop, ivs);
+      
+      // 只允许一侧为常数
+      if (expr0.base1 && !expr1.base1 && !expr1.base2 && expr1.offset) {
+        if (DEBUG >= 2) {
+          std::cout << "        -> BIV * constant pattern" << std::endl;
+        }
+        return {expr0.base1, nullptr, expr0.factor1 * expr1.offset, 0, expr0.offset * expr1.offset, true, true};
+      }
+      if (!expr0.base1 && !expr0.base2 && expr0.offset && expr1.base1) {
+        if (DEBUG >= 2) {
+          std::cout << "        -> Constant * BIV pattern" << std::endl;
+        }
+        return {expr1.base1, nullptr, expr1.factor1 * expr0.offset, 0, expr1.offset * expr0.offset, true, true};
+      }
+      // 双BIV乘法不支持
+      if (DEBUG >= 2) {
+        std::cout << "        -> Multiplication pattern not supported" << std::endl;
+      }
+    }
+    
+    // 除法：BIV/const（仅当const是2的幂时）
+    if (kind == Instruction::Kind::kDiv) {
+      if (DEBUG >= 2) {
+        std::cout << "        -> Analyzing division" << std::endl;
+      }
+      auto expr0 = analyzeLinearExpr(inst->getOperand(0), loop, ivs);
+      auto expr1 = analyzeLinearExpr(inst->getOperand(1), loop, ivs);
+      
+      // 只支持 BIV / 2^n 形式
+      if (expr0.base1 && !expr1.base1 && !expr1.base2 && expr1.offset > 0) {
+        // 检查是否为2的幂
+        int divisor = expr1.offset;
+        if ((divisor & (divisor - 1)) == 0) { // 2的幂检查
+          if (DEBUG >= 2) {
+            std::cout << "        -> BIV / power_of_2 pattern (divisor=" << divisor << ")" << std::endl;
+          }
+          // 对于除法，我们记录为特殊的归纳变量模式
+          // factor表示除数（用于后续强度削弱）
+          return {expr0.base1, nullptr, -divisor, 0, expr0.offset / divisor, true, true};
+        }
+      }
+      if (DEBUG >= 2) {
+        std::cout << "        -> Division pattern not supported (not power of 2)" << std::endl;
+      }
+    }
+    
+    // 取模：BIV % const（仅当const是2的幂时）
+    if (kind == Instruction::Kind::kRem) {
+      if (DEBUG >= 2) {
+        std::cout << "        -> Analyzing remainder" << std::endl;
+      }
+      auto expr0 = analyzeLinearExpr(inst->getOperand(0), loop, ivs);
+      auto expr1 = analyzeLinearExpr(inst->getOperand(1), loop, ivs);
+      
+      // 只支持 BIV % 2^n 形式
+      if (expr0.base1 && !expr1.base1 && !expr1.base2 && expr1.offset > 0) {
+        // 检查是否为2的幂
+        int modulus = expr1.offset;
+        if ((modulus & (modulus - 1)) == 0) { // 2的幂检查
+          if (DEBUG >= 2) {
+            std::cout << "        -> BIV % power_of_2 pattern (modulus=" << modulus << ")" << std::endl;
+          }
+          // 对于取模，我们记录为特殊的归纳变量模式
+          // 使用负的模数来区分取模和除法
+          return {expr0.base1, nullptr, -10000 - modulus, 0, 0, true, true}; // 特殊标记
+        }
+      }
+      if (DEBUG >= 2) {
+        std::cout << "        -> Remainder pattern not supported (not power of 2)" << std::endl;
+      }
+    }
+  }
+  
+  // 其它情况
+  if (DEBUG >= 2) {
+    std::cout << "        -> Other case: not linear" << std::endl;
+  }
+  return {nullptr, nullptr, 0, 0, 0, false, false};
+}
+
+void LoopCharacteristicsPass::identifyBasicLoopInvariants(Loop* loop, LoopCharacteristics* characteristics) {
+  // 经典推进法：反复遍历，直到收敛 TODO：优化
+  bool changed;
+  std::unordered_set<Value*> invariants = characteristics->loopInvariants; // 可能为空
+
+  do {
+    changed = false;
+    for (BasicBlock* bb : loop->getBlocks()) {
+      for (auto& inst : bb->getInstructions()) {
+        Instruction* I = inst.get();
+        // 跳过phi和terminator
+        if (dynamic_cast<PhiInst*>(I)) continue;
+        if (I->isTerminator()) continue;
+        if (invariants.count(I)) continue;
+
+        if (isClassicLoopInvariant(I, loop, invariants)) {
+          invariants.insert(I);
+          characteristics->invariantInsts.insert(I);
+          if (DEBUG)
+            std::cout << "    Found loop invariant: " << I->getName() << std::endl;
+          changed = true;
+        }
+      }
+    }
+  } while (changed);
+
+  characteristics->loopInvariants = std::move(invariants);
+}
+
+void LoopCharacteristicsPass::analyzeBasicLoopBounds(Loop* loop, LoopCharacteristics* characteristics) {
+  // 简化的基础边界分析
+  // 检查是否有静态可确定的循环次数（简化版本）
+  if (characteristics->isCountingLoop && !characteristics->InductionVars.empty()) {
+    // 简化：如果是计数循环且有基本归纳变量，尝试确定循环次数
+    if (characteristics->instructionCount < 10) {
+      characteristics->staticTripCount = 100; // 简化估计
+      characteristics->hasKnownBounds = true;
+      
+      if (DEBUG) {
+        std::cout << "    Estimated static trip count: " << *characteristics->staticTripCount << std::endl;
+      }
+    }
+  }
+}
+
+void LoopCharacteristicsPass::evaluateBasicOptimizationOpportunities(Loop* loop, LoopCharacteristics* characteristics) {
+  // 评估基础循环展开机会
+  characteristics->benefitsFromUnrolling = 
+    characteristics->isInnermost && 
+    characteristics->instructionCount > 3 && 
+    characteristics->instructionCount < 50 &&
+    !characteristics->hasComplexControlFlow;
+    
+  if (characteristics->benefitsFromUnrolling) {
+    // 基于循环体大小估算展开因子
+    if (characteristics->instructionCount <= 5) characteristics->suggestedUnrollFactor = 8;
+    else if (characteristics->instructionCount <= 10) characteristics->suggestedUnrollFactor = 4;
+    else if (characteristics->instructionCount <= 20) characteristics->suggestedUnrollFactor = 2;
+    else characteristics->suggestedUnrollFactor = 1;
+  }
+    
+  if (DEBUG) {
+    if (characteristics->benefitsFromUnrolling) {
+      std::cout << "    Loop " << loop->getName() << " benefits from UNROLLING (factor=" 
+                << characteristics->suggestedUnrollFactor << ")" << std::endl;
+    }
+  }
+}
+
+// ========== 辅助方法实现 ==========
+
+// 递归识别DIV，支持线性与复杂归纳变量
+void LoopCharacteristicsPass::findDerivedInductionVars(
+    Value* root,
+    Value* base, // 只传单一BIV base
+    Loop* loop,
+    std::vector<std::unique_ptr<InductionVarInfo>>& ivs,
+    std::set<Value*>& visited)
+{
+  if (visited.count(root)) return;
+  visited.insert(root);
+
+  if (DEBUG) {
+    std::cout << "      Analyzing uses of: " << root->getName() << std::endl;
+  }
+
+  for (auto use : root->getUses()) {
+    auto user = use->getUser();
+    Instruction* inst = dynamic_cast<Instruction*>(user);
+    if (!inst) continue;
+    if (!loop->contains(inst->getParent())) {
+      if (DEBUG) {
+        std::cout << "      Skipping user outside loop: " << inst->getName() << std::endl;
+      }
+      continue;
+    }
+
+    if (DEBUG) {
+      std::cout << "      Checking instruction: " << inst->getName() 
+                << " (kind: " << static_cast<int>(inst->getKind()) << ")" << std::endl;
+    }
+
+    // 线性归约分析
+    auto expr = analyzeLinearExpr(inst, loop, ivs);
+
+    if (!expr.valid) {
+      if (DEBUG) {
+        std::cout << "      Linear expression analysis failed for: " << inst->getName() << std::endl;
+      }
+      // 复杂非线性归纳变量，作为kCmplx记录（假如你想追踪）
+      // 这里假设expr.base1、base2都有效才记录double
+      if (expr.base1 && expr.base2) {
+        if (DEBUG) {
+          std::cout << "      [DIV-COMPLEX] Creating complex derived IV: " << inst->getName() 
+                    << " with bases: " << expr.base1->getName() << ", " << expr.base2->getName() << std::endl;
+        }
+        ivs.push_back(InductionVarInfo::createDoubleDIV(inst, inst->getKind(), expr.base1, expr.base2, 0, expr.offset));
+      }
+      continue;
+    }
+
+    // 单BIV线性
+    if (expr.base1 && !expr.base2) {
+      // 检查这个指令是否已经是一个已知的IV（特别是BIV），避免重复创建
+      bool alreadyExists = false;
+      for (const auto& existingIV : ivs) {
+        if (existingIV->div == inst) {
+          alreadyExists = true;
+          if (DEBUG) {
+            std::cout << "      [DIV-SKIP] Instruction " << inst->getName() 
+                      << " already exists as IV, skipping creation" << std::endl;
+          }
+          break;
+        }
+      }
+      
+      if (!alreadyExists) {
+        if (DEBUG) {
+          std::cout << "      [DIV-LINEAR] Creating single-base derived IV: " << inst->getName() 
+                    << " with base: " << expr.base1->getName() 
+                    << ", factor: " << expr.factor1 
+                    << ", offset: " << expr.offset << std::endl;
+        }
+        ivs.push_back(InductionVarInfo::createSingleDIV(inst, inst->getKind(), expr.base1, expr.factor1, expr.offset));
+        findDerivedInductionVars(inst, expr.base1, loop, ivs, visited);
+      }
+    }
+    // 双BIV线性
+    else if (expr.base1 && expr.base2) {
+      if (DEBUG) {
+        std::cout << "      [DIV-COMPLEX] Creating double-base derived IV: " << inst->getName() 
+                  << " with bases: " << expr.base1->getName() << ", " << expr.base2->getName() 
+                  << ", offset: " << expr.offset << std::endl;
+      }
+      ivs.push_back(InductionVarInfo::createDoubleDIV(inst, inst->getKind(), expr.base1, expr.base2, 0, expr.offset));
+      // 双BIV情形一般不再递归下游
+    }
+  }
+
+  if (DEBUG) {
+    std::cout << "      Finished analyzing uses of: " << root->getName() << std::endl;
+  }
+}
+
+// 递归/推进式判定
+bool LoopCharacteristicsPass::isClassicLoopInvariant(Value* val, Loop* loop, const std::unordered_set<Value*>& invariants) {
+  // 1. 常量
+  if (auto* constval = dynamic_cast<ConstantValue*>(val)) return true;
+
+  // 2. 参数（函数参数）通常不在任何BasicBlock内，直接判定为不变量
+  if (auto* arg = dynamic_cast<Argument*>(val)) return true;
+
+  // 3. 指令且定义在循环外
+  if (auto* inst = dynamic_cast<Instruction*>(val)) {
+    if (!loop->contains(inst->getParent()))
+      return true;
+
+    // 4. 跳转 phi指令 副作用 不外提
+    if (inst->isTerminator() || inst->isPhi() || sideEffectAnalysis->hasSideEffect(inst))
+      return false;
+
+    // 5. 所有操作数都是不变量
+    for (size_t i = 0; i < inst->getNumOperands(); ++i) {
+      Value* op = inst->getOperand(i);
+      if (!isClassicLoopInvariant(op, loop, invariants) && !invariants.count(op))
+        return false;
+    }
+    return true;
+  }
+  // 其它情况
+  return false;
+}
+
+bool LoopCharacteristicsPass::hasSimpleMemoryPattern(Loop* loop) {
+  // 检查是否有简单的内存访问模式
+  return true; // 暂时简化处理
+}
+
+} // namespace sysy

src/midend/Pass/Analysis/LoopVectorization.cpp

@@ -0,0 +1,803 @@
+#include "LoopVectorization.h"
+#include "Dom.h"
+#include "Loop.h"
+#include "Liveness.h"
+#include "AliasAnalysis.h" 
+#include "SideEffectAnalysis.h"
+#include <iostream>
+#include <algorithm>
+#include <cmath>
+#include <set>
+
+extern int DEBUG;
+
+namespace sysy {
+
+// 定义 Pass 的唯一 ID
+void *LoopVectorizationPass::ID = (void *)&LoopVectorizationPass::ID;
+
+std::vector<int> DependenceVector::getDirectionVector() const {
+  std::vector<int> direction;
+  direction.reserve(distances.size());
+  
+  for (int dist : distances) {
+    if (dist > 0) direction.push_back(1);       // 前向依赖
+    else if (dist < 0) direction.push_back(-1); // 后向依赖  
+    else direction.push_back(0);                // 无依赖
+  }
+  
+  return direction;
+}
+
+bool DependenceVector::isVectorizationSafe() const {
+  if (!isKnown) return false; // 未知依赖，不安全
+  
+  // 对于向量化，我们主要关心最内层循环的依赖
+  if (distances.empty()) return true;
+  
+  int innermostDistance = distances.back(); // 最内层循环的距离
+  
+  // 前向依赖 (距离 > 0) 通常是安全的，可以通过调整向量化顺序处理
+  // 后向依赖 (距离 < 0) 通常不安全，会阻止向量化
+  // 距离 = 0 表示同一迭代内的依赖，通常安全
+  
+  return innermostDistance >= 0;
+}
+
+size_t LoopVectorizationResult::getVectorizableLoopCount() const {
+  size_t count = 0;
+  for (const auto& [loop, analysis] : VectorizationMap) {
+    if (analysis.isVectorizable) count++;
+  }
+  return count;
+}
+
+size_t LoopVectorizationResult::getParallelizableLoopCount() const {
+  size_t count = 0;
+  for (const auto& [loop, analysis] : ParallelizationMap) {
+    if (analysis.isParallelizable) count++;
+  }
+  return count;
+}
+
+std::vector<Loop*> LoopVectorizationResult::getVectorizationCandidates() const {
+  std::vector<Loop*> candidates;
+  for (const auto& [loop, analysis] : VectorizationMap) {
+    if (analysis.isVectorizable) {
+      candidates.push_back(loop);
+    }
+  }
+  
+  // 按建议的向量宽度排序，优先处理收益更大的循环
+  std::sort(candidates.begin(), candidates.end(), 
+    [this](Loop* a, Loop* b) {
+      const auto& analysisA = VectorizationMap.at(a);
+      const auto& analysisB = VectorizationMap.at(b);
+      return analysisA.suggestedVectorWidth > analysisB.suggestedVectorWidth;
+    });
+  
+  return candidates;
+}
+
+std::vector<Loop*> LoopVectorizationResult::getParallelizationCandidates() const {
+  std::vector<Loop*> candidates;
+  for (const auto& [loop, analysis] : ParallelizationMap) {
+    if (analysis.isParallelizable) {
+      candidates.push_back(loop);
+    }
+  }
+  
+  // 按建议的线程数排序
+  std::sort(candidates.begin(), candidates.end(),
+    [this](Loop* a, Loop* b) {
+      const auto& analysisA = ParallelizationMap.at(a);
+      const auto& analysisB = ParallelizationMap.at(b);
+      return analysisA.suggestedThreadCount > analysisB.suggestedThreadCount;
+    });
+  
+  return candidates;
+}
+
+void LoopVectorizationResult::print() const {
+  if (!DEBUG) return;
+
+  std::cout << "\n--- Loop Vectorization/Parallelization Analysis Results for Function: " 
+            << AssociatedFunction->getName() << " ---" << std::endl;
+
+  if (VectorizationMap.empty() && ParallelizationMap.empty()) {
+    std::cout << "  No vectorization/parallelization analysis results." << std::endl;
+    return;
+  }
+
+  // 统计信息
+  std::cout << "\n=== Summary ===" << std::endl;
+  std::cout << "Total Loops Analyzed: " << VectorizationMap.size() << std::endl;
+  std::cout << "Vectorizable Loops: " << getVectorizableLoopCount() << std::endl;
+  std::cout << "Parallelizable Loops: " << getParallelizableLoopCount() << std::endl;
+
+  // 详细分析结果
+  for (const auto& [loop, vecAnalysis] : VectorizationMap) {
+    std::cout << "\n--- Loop: " << loop->getName() << " ---" << std::endl;
+    
+    // 向量化分析 (暂时搁置)
+    std::cout << "  Vectorization: " << (vecAnalysis.isVectorizable ? "YES" : "NO") << std::endl;
+    if (!vecAnalysis.preventingFactors.empty()) {
+      std::cout << "    Preventing Factors: ";
+      for (const auto& factor : vecAnalysis.preventingFactors) {
+        std::cout << factor << " ";
+      }
+      std::cout << std::endl;
+    }
+    
+    // 并行化分析
+    auto parallelIt = ParallelizationMap.find(loop);
+    if (parallelIt != ParallelizationMap.end()) {
+      const auto& parAnalysis = parallelIt->second;
+      std::cout << "  Parallelization: " << (parAnalysis.isParallelizable ? "YES" : "NO") << std::endl;
+      if (parAnalysis.isParallelizable) {
+        std::cout << "    Suggested Thread Count: " << parAnalysis.suggestedThreadCount << std::endl;
+        if (parAnalysis.requiresReduction) {
+          std::cout << "    Requires Reduction: Yes" << std::endl;
+        }
+        if (parAnalysis.requiresBarrier) {
+          std::cout << "    Requires Barrier: Yes" << std::endl;
+        }
+      } else if (!parAnalysis.preventingFactors.empty()) {
+        std::cout << "    Preventing Factors: ";
+        for (const auto& factor : parAnalysis.preventingFactors) {
+          std::cout << factor << " ";
+        }
+        std::cout << std::endl;
+      }
+    }
+    
+    // 依赖关系
+    auto depIt = DependenceMap.find(loop);
+    if (depIt != DependenceMap.end()) {
+      const auto& dependences = depIt->second;
+      std::cout << "  Dependences: " << dependences.size() << " found" << std::endl;
+      for (const auto& dep : dependences) {
+        if (dep.dependenceVector.isKnown) {
+          std::cout << "    " << dep.source->getName() << " -> " << dep.sink->getName();
+          std::cout << " [";
+          for (size_t i = 0; i < dep.dependenceVector.distances.size(); ++i) {
+            if (i > 0) std::cout << ",";
+            std::cout << dep.dependenceVector.distances[i];
+          }
+          std::cout << "]" << std::endl;
+        }
+      }
+    }
+  }
+  
+  std::cout << "-----------------------------------------------" << std::endl;
+}
+
+bool LoopVectorizationPass::runOnFunction(Function *F, AnalysisManager &AM) {
+  if (F->getBasicBlocks().empty()) {
+    CurrentResult = std::make_unique<LoopVectorizationResult>(F);
+    return false;
+  }
+
+  if (DEBUG) {
+    std::cout << "Running LoopVectorizationPass on function: " << F->getName() << std::endl;
+  }
+
+  // 获取循环分析结果
+  auto* loopAnalysisResult = AM.getAnalysisResult<LoopAnalysisResult, LoopAnalysisPass>(F);
+  if (!loopAnalysisResult || !loopAnalysisResult->hasLoops()) {
+    CurrentResult = std::make_unique<LoopVectorizationResult>(F);
+    return false;
+  }
+
+  // 获取循环特征分析结果
+  auto* loopCharacteristics = AM.getAnalysisResult<LoopCharacteristicsResult, LoopCharacteristicsPass>(F);
+  if (!loopCharacteristics) {
+    if (DEBUG) {
+      std::cout << "Warning: LoopCharacteristics analysis not available" << std::endl;
+    }
+  }
+
+  // 获取别名分析结果
+  auto* aliasAnalysis = AM.getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(F);
+  
+  // 获取副作用分析结果
+  auto* sideEffectAnalysis = AM.getAnalysisResult<SideEffectAnalysisResult, SysYSideEffectAnalysisPass>();
+
+  CurrentResult = std::make_unique<LoopVectorizationResult>(F);
+
+  // 分析每个循环的向量化/并行化可行性
+  for (const auto& loop_ptr : loopAnalysisResult->getAllLoops()) {
+    Loop* loop = loop_ptr.get();
+    
+    // 获取该循环的特征信息
+    LoopCharacteristics* characteristics = nullptr;
+    if (loopCharacteristics) {
+      characteristics = const_cast<LoopCharacteristics*>(loopCharacteristics->getCharacteristics(loop));
+    }
+    
+    analyzeLoop(loop, characteristics, aliasAnalysis, sideEffectAnalysis);
+  }
+
+  if (DEBUG) {
+    std::cout << "LoopVectorizationPass completed. Found " 
+              << CurrentResult->getVectorizableLoopCount() << " vectorizable loops, "
+              << CurrentResult->getParallelizableLoopCount() << " parallelizable loops" << std::endl;
+  }
+
+  return false; // 分析遍不修改IR
+}
+
+void LoopVectorizationPass::analyzeLoop(Loop* loop, LoopCharacteristics* characteristics, 
+                                       AliasAnalysisResult* aliasAnalysis, SideEffectAnalysisResult* sideEffectAnalysis) {
+  if (DEBUG) {
+    std::cout << "  Analyzing advanced features for loop: " << loop->getName() << std::endl;
+  }
+
+  // 1. 计算精确依赖向量
+  auto dependences = computeDependenceVectors(loop, aliasAnalysis);
+  CurrentResult->addDependenceAnalysis(loop, dependences);
+
+  // 2. 分析向量化可行性 (暂时搁置，总是返回不可向量化)
+  auto vecAnalysis = analyzeVectorizability(loop, dependences, characteristics);
+  CurrentResult->addVectorizationAnalysis(loop, vecAnalysis);
+
+  // 3. 分析并行化可行性 
+  auto parAnalysis = analyzeParallelizability(loop, dependences, characteristics);
+  CurrentResult->addParallelizationAnalysis(loop, parAnalysis);
+}
+
+// ========== 依赖向量分析实现 ==========
+
+std::vector<PreciseDependence> LoopVectorizationPass::computeDependenceVectors(Loop* loop, 
+                                                                              AliasAnalysisResult* aliasAnalysis) {
+  std::vector<PreciseDependence> dependences;
+  std::vector<Instruction*> memoryInsts;
+  
+  // 收集所有内存操作指令
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      if (dynamic_cast<LoadInst*>(inst.get()) || dynamic_cast<StoreInst*>(inst.get())) {
+        memoryInsts.push_back(inst.get());
+      }
+    }
+  }
+  
+  // 分析每对内存操作之间的依赖关系
+  for (size_t i = 0; i < memoryInsts.size(); ++i) {
+    for (size_t j = i + 1; j < memoryInsts.size(); ++j) {
+      Instruction* inst1 = memoryInsts[i];
+      Instruction* inst2 = memoryInsts[j];
+      
+      Value* ptr1 = nullptr;
+      Value* ptr2 = nullptr;
+      
+      if (auto* load = dynamic_cast<LoadInst*>(inst1)) {
+        ptr1 = load->getPointer();
+      } else if (auto* store = dynamic_cast<StoreInst*>(inst1)) {
+        ptr1 = store->getPointer();
+      }
+      
+      if (auto* load = dynamic_cast<LoadInst*>(inst2)) {
+        ptr2 = load->getPointer();
+      } else if (auto* store = dynamic_cast<StoreInst*>(inst2)) {
+        ptr2 = store->getPointer();
+      }
+      
+      if (!ptr1 || !ptr2) continue;
+      
+      // 检查是否可能存在别名关系
+      bool mayAlias = false;
+      if (aliasAnalysis) {
+        mayAlias = aliasAnalysis->queryAlias(ptr1, ptr2) != AliasType::NO_ALIAS;
+      } else {
+        mayAlias = (ptr1 != ptr2); // 保守估计
+      }
+      
+      if (mayAlias) {
+        // 创建依赖关系
+        PreciseDependence dep(loop->getLoopDepth());
+        dep.source = inst1;
+        dep.sink = inst2;
+        dep.memoryLocation = ptr1;
+        
+        // 确定依赖类型
+        bool isStore1 = dynamic_cast<StoreInst*>(inst1) != nullptr;
+        bool isStore2 = dynamic_cast<StoreInst*>(inst2) != nullptr;
+        
+        if (isStore1 && !isStore2) {
+          dep.type = DependenceType::TRUE_DEPENDENCE; // Write -> Read (RAW)
+        } else if (!isStore1 && isStore2) {
+          dep.type = DependenceType::ANTI_DEPENDENCE; // Read -> Write (WAR)
+        } else if (isStore1 && isStore2) {
+          dep.type = DependenceType::OUTPUT_DEPENDENCE; // Write -> Write (WAW)
+        } else {
+          continue; // Read -> Read (RAR) - 跳过，不是真正的依赖
+        }
+        
+        // 计算依赖向量
+        dep.dependenceVector = computeAccessDependence(inst1, inst2, loop);
+        
+        // 判断是否允许并行化
+        dep.allowsParallelization = dep.dependenceVector.isLoopIndependent() || 
+                                   (dep.dependenceVector.isKnown && 
+                                    std::all_of(dep.dependenceVector.distances.begin(), 
+                                               dep.dependenceVector.distances.end(),
+                                               [](int d) { return d >= 0; }));
+        
+        dependences.push_back(dep);
+        
+        if (DEBUG && dep.dependenceVector.isKnown) {
+          std::cout << "        Found dependence: " << inst1->getName() 
+                    << " -> " << inst2->getName() << " [";
+          for (size_t k = 0; k < dep.dependenceVector.distances.size(); ++k) {
+            if (k > 0) std::cout << ",";
+            std::cout << dep.dependenceVector.distances[k];
+          }
+          std::cout << "]" << std::endl;
+        }
+      }
+    }
+  }
+  
+  return dependences;
+}
+
+DependenceVector LoopVectorizationPass::computeAccessDependence(Instruction* inst1, Instruction* inst2, Loop* loop) {
+  DependenceVector depVec(loop->getLoopDepth());
+  
+  Value* ptr1 = nullptr;
+  Value* ptr2 = nullptr;
+  
+  if (auto* load = dynamic_cast<LoadInst*>(inst1)) {
+    ptr1 = load->getPointer();
+  } else if (auto* store = dynamic_cast<StoreInst*>(inst1)) {
+    ptr1 = store->getPointer();
+  }
+  
+  if (auto* load = dynamic_cast<LoadInst*>(inst2)) {
+    ptr2 = load->getPointer();
+  } else if (auto* store = dynamic_cast<StoreInst*>(inst2)) {
+    ptr2 = store->getPointer();
+  }
+  
+  if (!ptr1 || !ptr2) return depVec;
+  
+  // 尝试分析仿射关系
+  if (areAccessesAffinelyRelated(ptr1, ptr2, loop)) {
+    auto coeff1 = extractInductionCoefficients(ptr1, loop);
+    auto coeff2 = extractInductionCoefficients(ptr2, loop);
+    
+    if (coeff1.size() == coeff2.size()) {
+      depVec.isKnown = true;
+      depVec.isConstant = true;
+      
+      for (size_t i = 0; i < coeff1.size(); ++i) {
+        depVec.distances[i] = coeff2[i] - coeff1[i];
+      }
+    }
+  }
+  
+  return depVec;
+}
+
+bool LoopVectorizationPass::areAccessesAffinelyRelated(Value* ptr1, Value* ptr2, Loop* loop) {
+  // 简化实现：检查是否都是基于归纳变量的数组访问
+  // 真正的实现需要复杂的仿射关系分析
+  
+  // 检查是否为 GEP 指令
+  auto* gep1 = dynamic_cast<GetElementPtrInst*>(ptr1);
+  auto* gep2 = dynamic_cast<GetElementPtrInst*>(ptr2);
+  
+  if (!gep1 || !gep2) return false;
+  
+  // 检查是否访问同一个数组基址
+  if (gep1->getBasePointer() != gep2->getBasePointer()) return false;
+  
+  // 简化：假设都是仿射的
+  return true;
+}
+
+// ========== 向量化分析实现 (暂时搁置) ==========
+
+VectorizationAnalysis LoopVectorizationPass::analyzeVectorizability(Loop* loop, 
+                                                                   const std::vector<PreciseDependence>& dependences,
+                                                                   LoopCharacteristics* characteristics) {
+  VectorizationAnalysis analysis; // 构造函数已设置为不可向量化
+  
+  if (DEBUG) {
+    std::cout << "    Vectorization analysis: DISABLED (temporarily)" << std::endl;
+  }
+  
+  // 向量化功能暂时搁置，总是返回不可向量化
+  // 这里可以添加一些基本的诊断信息用于日志
+  if (!loop->isInnermost()) {
+    analysis.preventingFactors.push_back("Not innermost loop");
+  }
+  if (loop->getBlocks().size() > 1) {
+    analysis.preventingFactors.push_back("Complex control flow");
+  }
+  if (!dependences.empty()) {
+    analysis.preventingFactors.push_back("Has dependences (not analyzed in detail)");
+  }
+  
+  return analysis;
+}
+
+// ========== 并行化分析实现 ==========
+
+ParallelizationAnalysis LoopVectorizationPass::analyzeParallelizability(Loop* loop,
+                                                                       const std::vector<PreciseDependence>& dependences,
+                                                                       LoopCharacteristics* characteristics) {
+  ParallelizationAnalysis analysis;
+  
+  if (DEBUG) {
+    std::cout << "    Analyzing parallelizability for loop: " << loop->getName() << std::endl;
+    std::cout << "      Found " << dependences.size() << " dependences" << std::endl;
+  }
+  
+  // 按依赖类型分类分析
+  bool hasTrueDependences = false;
+  bool hasAntiDependences = false;
+  bool hasOutputDependences = false;
+  
+  for (const auto& dep : dependences) {
+    switch (dep.type) {
+      case DependenceType::TRUE_DEPENDENCE:
+        hasTrueDependences = true;
+        // 真依赖通常是最难处理的，需要检查是否为归约模式
+        if (dep.isReductionDependence) {
+          analysis.requiresReduction = true;
+          analysis.reductionVariables.insert(dep.memoryLocation);
+        } else {
+          analysis.preventingFactors.push_back("Non-reduction true dependence");
+        }
+        break;
+      case DependenceType::ANTI_DEPENDENCE:
+        hasAntiDependences = true;
+        // 反依赖可以通过变量私有化解决
+        analysis.privatizableVariables.insert(dep.memoryLocation);
+        break;
+      case DependenceType::OUTPUT_DEPENDENCE:
+        hasOutputDependences = true;
+        // 输出依赖可以通过变量私有化或原子操作解决
+        analysis.sharedVariables.insert(dep.memoryLocation);
+        break;
+    }
+  }
+  
+  // 确定并行化类型
+  analysis.parallelType = determineParallelizationType(loop, dependences);
+  
+  // 基于依赖类型评估可并行性
+  if (!hasTrueDependences && !hasOutputDependences) {
+    // 只有反依赖或无依赖，完全可并行
+    analysis.parallelType = ParallelizationAnalysis::EMBARRASSINGLY_PARALLEL;
+    analysis.isParallelizable = true;
+  } else if (analysis.requiresReduction) {
+    // 有归约模式，可以并行但需要特殊处理
+    analysis.parallelType = ParallelizationAnalysis::REDUCTION_PARALLEL;
+    analysis.isParallelizable = true;
+  } else if (hasTrueDependences) {
+    // 有非归约的真依赖，通常不能并行化
+    analysis.isParallelizable = false;
+    analysis.preventingFactors.push_back("Non-reduction loop-carried true dependences");
+  }
+  
+  if (analysis.isParallelizable) {
+    // 进一步分析并行化收益和成本
+    estimateParallelizationBenefit(loop, &analysis, characteristics);
+    analyzeSynchronizationNeeds(loop, &analysis, dependences);
+    analysis.suggestedThreadCount = estimateOptimalThreadCount(loop, characteristics);
+  }
+  
+  if (DEBUG) {
+    std::cout << "      Parallelizable: " << (analysis.isParallelizable ? "YES" : "NO") << std::endl;
+    if (analysis.isParallelizable) {
+      std::cout << "      Type: " << (int)analysis.parallelType << ", Threads: " << analysis.suggestedThreadCount << std::endl;
+    }
+  }
+  
+  return analysis;
+}
+
+bool LoopVectorizationPass::checkParallelizationLegality(Loop* loop, const std::vector<PreciseDependence>& dependences) {
+  // 检查所有依赖是否允许并行化
+  for (const auto& dep : dependences) {
+    if (!dep.allowsParallelization) {
+      return false;
+    }
+  }
+  
+  // 检查是否有无法并行化的操作
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      // 检查原子操作、同步操作等
+      if (auto* call = dynamic_cast<CallInst*>(inst.get())) {
+        // 简化：假设函数调用需要特殊处理
+        // 在实际实现中，需要分析函数的副作用
+        return false;
+      }
+    }
+  }
+  
+  return true;
+}
+
+int LoopVectorizationPass::estimateOptimalThreadCount(Loop* loop, LoopCharacteristics* characteristics) {
+  // 基于循环特征估计最优线程数
+  if (!characteristics) return 2;
+  
+  // 基于循环体大小和计算密度
+  int baseThreads = 2;
+  
+  if (characteristics->instructionCount > 50) baseThreads = 4;
+  if (characteristics->instructionCount > 200) baseThreads = 8;
+  
+  // 基于计算与内存比率调整
+  if (characteristics->computeToMemoryRatio > 2.0) {
+    baseThreads *= 2; // 计算密集型，可以使用更多线程
+  }
+  
+  return std::min(baseThreads, 16); // 限制最大线程数
+}
+
+// ========== 辅助方法实现 ==========
+
+bool LoopVectorizationPass::isConstantStride(Value* ptr, Loop* loop, int& stride) {
+  // 简化实现：检查是否为常量步长访问
+  stride = 1; // 默认步长
+  
+  auto* gep = dynamic_cast<GetElementPtrInst*>(ptr);
+  if (!gep) return false;
+  
+  // 检查最后一个索引是否为归纳变量 + 常量
+  if (gep->getNumIndices() > 0) {
+    Value* lastIndex = gep->getIndex(gep->getNumIndices() - 1);
+    
+    // 简化：假设是 i 或 i+c 的形式
+    if (auto* binInst = dynamic_cast<BinaryInst*>(lastIndex)) {
+      if (binInst->getKind() == Instruction::kAdd) {
+        // 检查是否为 i + constant
+        if (auto* constInt = dynamic_cast<ConstantInteger*>(binInst->getRhs())) {
+          stride = constInt->getInt();
+          return true;
+        }
+      }
+    }
+    
+    // 默认为步长1的连续访问
+    stride = 1;
+    return true;
+  }
+  
+  return false;
+}
+
+std::vector<int> LoopVectorizationPass::extractInductionCoefficients(Value* ptr, Loop* loop) {
+  // 简化实现：返回默认的仿射系数
+  std::vector<int> coefficients;
+  
+  // 假设是简单的 a[i] 形式，系数为 [0, 1]
+  coefficients.push_back(0); // 常数项
+  coefficients.push_back(1); // 归纳变量系数
+  
+  return coefficients;
+}
+
+// ========== 缺失的方法实现 ==========
+
+ParallelizationAnalysis::ParallelizationType LoopVectorizationPass::determineParallelizationType(
+    Loop* loop, const std::vector<PreciseDependence>& dependences) {
+  
+  // 检查是否有任何依赖
+  if (dependences.empty()) {
+    return ParallelizationAnalysis::EMBARRASSINGLY_PARALLEL;
+  }
+  
+  // 检查是否只有归约模式
+  bool hasReduction = false;
+  bool hasOtherDependences = false;
+  
+  for (const auto& dep : dependences) {
+    if (dep.isReductionDependence) {
+      hasReduction = true;
+    } else if (dep.type == DependenceType::TRUE_DEPENDENCE) {
+      hasOtherDependences = true;
+    }
+  }
+  
+  if (hasReduction && !hasOtherDependences) {
+    return ParallelizationAnalysis::REDUCTION_PARALLEL;
+  } else if (!hasOtherDependences) {
+    return ParallelizationAnalysis::EMBARRASSINGLY_PARALLEL;
+  }
+  
+  return ParallelizationAnalysis::NONE;
+}
+
+void LoopVectorizationPass::analyzeReductionPatterns(Loop* loop, ParallelizationAnalysis* analysis) {
+  // 简化实现：查找常见的归约模式
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      if (auto* binInst = dynamic_cast<BinaryInst*>(inst.get())) {
+        if (binInst->getKind() == Instruction::kAdd || binInst->getKind() == Instruction::kMul) {
+          // 检查是否为累加/累乘模式
+          Value* lhs = binInst->getLhs();
+          if (hasReductionPattern(lhs, loop)) {
+            analysis->requiresReduction = true;
+            analysis->reductionVariables.insert(lhs);
+          }
+        }
+      }
+    }
+  }
+}
+
+void LoopVectorizationPass::analyzeMemoryAccessPatterns(Loop* loop, ParallelizationAnalysis* analysis, 
+                                                       AliasAnalysisResult* aliasAnalysis) {
+  std::vector<Value*> memoryAccesses;
+  
+  // 收集所有内存访问
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      if (auto* load = dynamic_cast<LoadInst*>(inst.get())) {
+        memoryAccesses.push_back(load->getPointer());
+      } else if (auto* store = dynamic_cast<StoreInst*>(inst.get())) {
+        memoryAccesses.push_back(store->getPointer());
+      }
+    }
+  }
+  
+  // 分析内存访问独立性
+  bool hasIndependentAccess = true;
+  for (size_t i = 0; i < memoryAccesses.size(); ++i) {
+    for (size_t j = i + 1; j < memoryAccesses.size(); ++j) {
+      if (!isIndependentMemoryAccess(memoryAccesses[i], memoryAccesses[j], loop)) {
+        hasIndependentAccess = false;
+        analysis->hasMemoryConflicts = true;
+      }
+    }
+  }
+  
+  analysis->hasIndependentAccess = hasIndependentAccess;
+}
+
+void LoopVectorizationPass::estimateParallelizationBenefit(Loop* loop, ParallelizationAnalysis* analysis,
+                                                          LoopCharacteristics* characteristics) {
+  if (!analysis->isParallelizable) {
+    analysis->parallelizationBenefit = 0.0;
+    return;
+  }
+  
+  // 基于计算复杂度和并行度计算收益
+  double workComplexity = estimateWorkComplexity(loop);
+  double parallelFraction = 1.0; // 假设完全可并行
+  
+  // 根据依赖调整并行度
+  if (analysis->requiresReduction) {
+    parallelFraction *= 0.8; // 归约降低并行效率
+  }
+  if (analysis->hasMemoryConflicts) {
+    parallelFraction *= 0.6; // 内存冲突降低效率
+  }
+  
+  // Amdahl定律估算
+  double serialFraction = 1.0 - parallelFraction;
+  int threadCount = analysis->suggestedThreadCount;
+  double speedup = 1.0 / (serialFraction + parallelFraction / threadCount);
+  
+  analysis->parallelizationBenefit = std::min((speedup - 1.0) / threadCount, 1.0);
+  
+  // 估算同步和通信开销
+  analysis->synchronizationCost = analysis->requiresBarrier ? 100 : 0;
+  analysis->communicationCost = analysis->sharedVariables.size() * 50;
+}
+
+void LoopVectorizationPass::identifyPrivatizableVariables(Loop* loop, ParallelizationAnalysis* analysis) {
+  // 简化实现：标识循环内定义的变量为可私有化
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      if (!inst->getType()->isVoid()) {
+        // 如果变量只在循环内使用，可能可以私有化
+        bool onlyUsedInLoop = true;
+        for (auto& use : inst->getUses()) {
+          if (auto* userInst = dynamic_cast<Instruction*>(use->getUser())) {
+            if (!loop->contains(userInst->getParent())) {
+              onlyUsedInLoop = false;
+              break;
+            }
+          }
+        }
+        
+        if (onlyUsedInLoop) {
+          analysis->privatizableVariables.insert(inst.get());
+        }
+      }
+    }
+  }
+}
+
+void LoopVectorizationPass::analyzeSynchronizationNeeds(Loop* loop, ParallelizationAnalysis* analysis,
+                                                       const std::vector<PreciseDependence>& dependences) {
+  // 根据依赖类型确定同步需求
+  for (const auto& dep : dependences) {
+    if (dep.type == DependenceType::OUTPUT_DEPENDENCE) {
+      analysis->requiresBarrier = true;
+      analysis->sharedVariables.insert(dep.memoryLocation);
+    }
+  }
+  
+  // 如果有归约，需要特殊的归约同步
+  if (analysis->requiresReduction) {
+    analysis->requiresBarrier = true;
+  }
+}
+
+bool LoopVectorizationPass::isIndependentMemoryAccess(Value* ptr1, Value* ptr2, Loop* loop) {
+  // 简化实现：基本的独立性检查
+  if (ptr1 == ptr2) return false;
+  
+  // 如果是不同的基址，认为是独立的
+  auto* gep1 = dynamic_cast<GetElementPtrInst*>(ptr1);
+  auto* gep2 = dynamic_cast<GetElementPtrInst*>(ptr2);
+  
+  if (gep1 && gep2) {
+    if (gep1->getBasePointer() != gep2->getBasePointer()) {
+      return true; // 不同的基址
+    }
+    // 相同基址，需要更精细的分析（这里简化为不独立）
+    return false;
+  }
+  
+  return true; // 默认认为独立
+}
+
+double LoopVectorizationPass::estimateWorkComplexity(Loop* loop) {
+  double complexity = 0.0;
+  
+  for (BasicBlock* bb : loop->getBlocks()) {
+    for (auto& inst : bb->getInstructions()) {
+      // 基于指令类型分配复杂度权重
+      if (auto* binInst = dynamic_cast<BinaryInst*>(inst.get())) {
+        switch (binInst->getKind()) {
+          case Instruction::kAdd:
+          case Instruction::kSub:
+            complexity += 1.0;
+            break;
+          case Instruction::kMul:
+            complexity += 3.0;
+            break;
+          case Instruction::kDiv:
+            complexity += 10.0;
+            break;
+          default:
+            complexity += 2.0;
+        }
+      } else if (dynamic_cast<LoadInst*>(inst.get()) || dynamic_cast<StoreInst*>(inst.get())) {
+        complexity += 2.0; // 内存访问
+      } else {
+        complexity += 1.0; // 其他指令
+      }
+    }
+  }
+  
+  return complexity;
+}
+
+bool LoopVectorizationPass::hasReductionPattern(Value* var, Loop* loop) {
+  // 简化实现：检查是否为简单的累加/累乘模式
+  for (auto& use : var->getUses()) {
+    if (auto* binInst = dynamic_cast<BinaryInst*>(use->getUser())) {
+      if (binInst->getKind() == Instruction::kAdd || binInst->getKind() == Instruction::kMul) {
+        // 检查是否为 var = var op something 的模式
+        if (binInst->getLhs() == var || binInst->getRhs() == var) {
+          return true;
+        }
+      }
+    }
+  }
+  return false;
+}
+
+} // namespace sysy

src/midend/Pass/Analysis/SideEffectAnalysis.cpp

@@ -0,0 +1,402 @@
+#include "SideEffectAnalysis.h"
+#include "AliasAnalysis.h"
+#include "CallGraphAnalysis.h"
+#include "SysYIRPrinter.h"
+#include <iostream>
+
+namespace sysy {
+
+// 副作用分析遍的静态 ID
+void *SysYSideEffectAnalysisPass::ID = (void *)&SysYSideEffectAnalysisPass::ID;
+
+// ======================================================================
+// SideEffectAnalysisResult 类的实现
+// ======================================================================
+
+SideEffectAnalysisResult::SideEffectAnalysisResult() { initializeKnownFunctions(); }
+
+const SideEffectInfo &SideEffectAnalysisResult::getInstructionSideEffect(Instruction *inst) const {
+  auto it = instructionSideEffects.find(inst);
+  if (it != instructionSideEffects.end()) {
+    return it->second;
+  }
+  // 返回默认的无副作用信息
+  static SideEffectInfo noEffect;
+  return noEffect;
+}
+
+const SideEffectInfo &SideEffectAnalysisResult::getFunctionSideEffect(Function *func) const {
+  auto it = functionSideEffects.find(func);
+  if (it != functionSideEffects.end()) {
+    return it->second;
+  }
+  // 返回默认的无副作用信息
+  static SideEffectInfo noEffect;
+  return noEffect;
+}
+
+void SideEffectAnalysisResult::setInstructionSideEffect(Instruction *inst, const SideEffectInfo &info) {
+  instructionSideEffects[inst] = info;
+}
+
+void SideEffectAnalysisResult::setFunctionSideEffect(Function *func, const SideEffectInfo &info) {
+  functionSideEffects[func] = info;
+}
+
+bool SideEffectAnalysisResult::hasSideEffect(Instruction *inst) const {
+  const auto &info = getInstructionSideEffect(inst);
+  return info.type != SideEffectType::NO_SIDE_EFFECT;
+}
+
+bool SideEffectAnalysisResult::mayModifyMemory(Instruction *inst) const {
+  const auto &info = getInstructionSideEffect(inst);
+  return info.mayModifyMemory;
+}
+
+bool SideEffectAnalysisResult::mayModifyGlobal(Instruction *inst) const {
+  const auto &info = getInstructionSideEffect(inst);
+  return info.mayModifyGlobal;
+}
+
+bool SideEffectAnalysisResult::isPureFunction(Function *func) const {
+  const auto &info = getFunctionSideEffect(func);
+  return info.isPure;
+}
+
+void SideEffectAnalysisResult::initializeKnownFunctions() {
+  // SysY标准库函数的副作用信息
+
+  // I/O函数 - 有副作用
+  SideEffectInfo ioEffect;
+  ioEffect.type = SideEffectType::IO_OPERATION;
+  ioEffect.mayModifyGlobal = true;
+  ioEffect.mayModifyMemory = true;
+  ioEffect.mayCallFunction = true;
+  ioEffect.isPure = false;
+
+  // knownFunctions["printf"] = ioEffect;
+  // knownFunctions["scanf"] = ioEffect;
+  knownFunctions["getint"] = ioEffect;
+  knownFunctions["getch"] = ioEffect;
+  knownFunctions["getfloat"] = ioEffect;
+  knownFunctions["getarray"] = ioEffect;
+  knownFunctions["getfarray"] = ioEffect;
+  knownFunctions["putint"] = ioEffect;
+  knownFunctions["putch"] = ioEffect;
+  knownFunctions["putfloat"] = ioEffect;
+  knownFunctions["putarray"] = ioEffect;
+  knownFunctions["putfarray"] = ioEffect;
+
+  // 时间函数 - 有副作用
+  SideEffectInfo timeEffect;
+  timeEffect.type = SideEffectType::FUNCTION_CALL;
+  timeEffect.mayModifyGlobal = true;
+  timeEffect.mayModifyMemory = false;
+  timeEffect.mayCallFunction = true;
+  timeEffect.isPure = false;
+
+  knownFunctions["_sysy_starttime"] = timeEffect;
+  knownFunctions["_sysy_stoptime"] = timeEffect;
+}
+
+const SideEffectInfo *SideEffectAnalysisResult::getKnownFunctionSideEffect(const std::string &funcName) const {
+  auto it = knownFunctions.find(funcName);
+  return (it != knownFunctions.end()) ? &it->second : nullptr;
+}
+
+// ======================================================================
+// SysYSideEffectAnalysisPass 类的实现
+// ======================================================================
+
+bool SysYSideEffectAnalysisPass::runOnModule(Module *M, AnalysisManager &AM) {
+  if (DEBUG) {
+    std::cout << "Running SideEffect analysis on module" << std::endl;
+  }
+
+  // 创建分析结果（构造函数中已经调用了initializeKnownFunctions）
+  result = std::make_unique<SideEffectAnalysisResult>();
+
+  // 获取调用图分析结果
+  callGraphAnalysis = AM.getAnalysisResult<CallGraphAnalysisResult, CallGraphAnalysisPass>();
+  if (!callGraphAnalysis) {
+    std::cerr << "Warning: CallGraphAnalysis not available, falling back to conservative analysis" << std::endl;
+  }
+
+  // 按拓扑序分析函数，确保被调用函数先于调用者分析
+  if (callGraphAnalysis) {
+    // 使用调用图的拓扑排序结果
+    const auto &topOrder = callGraphAnalysis->getTopologicalOrder();
+
+    // 处理强连通分量（递归函数群）
+    const auto &sccs = callGraphAnalysis->getStronglyConnectedComponents();
+    for (const auto &scc : sccs) {
+      if (scc.size() > 1) {
+        // 多个函数的强连通分量，使用不动点算法
+        analyzeStronglyConnectedComponent(scc, AM);
+      } else {
+        // 单个函数，检查是否自递归
+        Function *func = scc[0];
+        if (callGraphAnalysis->isSelfRecursive(func)) {
+          // 自递归函数也需要不动点算法
+          analyzeStronglyConnectedComponent(scc, AM);
+        } else {
+          // 非递归函数，直接分析
+          SideEffectInfo funcEffect = analyzeFunction(func, AM);
+          result->setFunctionSideEffect(func, funcEffect);
+        }
+      }
+    }
+  } else {
+    // 没有调用图，保守地分析每个函数
+    for (auto &pair : M->getFunctions()) {
+      Function *func = pair.second.get();
+      SideEffectInfo funcEffect = analyzeFunction(func, AM);
+      result->setFunctionSideEffect(func, funcEffect);
+    }
+  }
+
+  if (DEBUG) {
+    std::cout << "---- Side Effect Analysis Results for Module ----\n";
+    for (auto &pair : M->getFunctions()) {
+      Function *func = pair.second.get();
+      const auto &funcInfo = result->getFunctionSideEffect(func);
+
+      std::cout << "Function " << func->getName() << ": ";
+      switch (funcInfo.type) {
+      case SideEffectType::NO_SIDE_EFFECT:
+        std::cout << "No Side Effect";
+        break;
+      case SideEffectType::MEMORY_WRITE:
+        std::cout << "Memory Write";
+        break;
+      case SideEffectType::FUNCTION_CALL:
+        std::cout << "Function Call";
+        break;
+      case SideEffectType::IO_OPERATION:
+        std::cout << "I/O Operation";
+        break;
+      case SideEffectType::UNKNOWN:
+        std::cout << "Unknown";
+        break;
+      }
+      std::cout << " (Pure: " << (funcInfo.isPure ? "Yes" : "No")
+                << ", Modifies Global: " << (funcInfo.mayModifyGlobal ? "Yes" : "No") << ")\n";
+    }
+    std::cout << "--------------------------------------------------\n";
+  }
+
+  return false; // Analysis passes return false since they don't modify the IR
+}
+
+std::unique_ptr<AnalysisResultBase> SysYSideEffectAnalysisPass::getResult() { return std::move(result); }
+
+SideEffectInfo SysYSideEffectAnalysisPass::analyzeFunction(Function *func, AnalysisManager &AM) {
+  SideEffectInfo functionSideEffect;
+
+  // 为每个指令分析副作用
+  for (auto &BB : func->getBasicBlocks()) {
+    for (auto &I : BB->getInstructions_Range()) {
+      Instruction *inst = I.get();
+      SideEffectInfo instEffect = analyzeInstruction(inst, func, AM);
+
+      // 记录指令的副作用信息
+      result->setInstructionSideEffect(inst, instEffect);
+
+      // 合并到函数级别的副作用信息中
+      functionSideEffect = functionSideEffect.merge(instEffect);
+    }
+  }
+
+  return functionSideEffect;
+}
+
+void SysYSideEffectAnalysisPass::analyzeStronglyConnectedComponent(const std::vector<Function *> &scc,
+                                                                   AnalysisManager &AM) {
+  // 使用不动点算法处理递归函数群
+  std::unordered_map<Function *, SideEffectInfo> currentEffects;
+  std::unordered_map<Function *, SideEffectInfo> previousEffects;
+
+  // 初始化：所有函数都假设为纯函数
+  for (Function *func : scc) {
+    SideEffectInfo initialEffect;
+    initialEffect.isPure = true;
+    currentEffects[func] = initialEffect;
+    result->setFunctionSideEffect(func, initialEffect);
+  }
+
+  bool converged = false;
+  int iterations = 0;
+  const int maxIterations = 10; // 防止无限循环
+
+  while (!converged && iterations < maxIterations) {
+    previousEffects = currentEffects;
+
+    // 重新分析每个函数
+    for (Function *func : scc) {
+      SideEffectInfo newEffect = analyzeFunction(func, AM);
+      currentEffects[func] = newEffect;
+      result->setFunctionSideEffect(func, newEffect);
+    }
+
+    // 检查是否收敛
+    converged = hasConverged(previousEffects, currentEffects);
+    iterations++;
+  }
+
+  if (iterations >= maxIterations) {
+    std::cerr << "Warning: SideEffect analysis did not converge for SCC after " << maxIterations << " iterations"
+              << std::endl;
+  }
+}
+
+bool SysYSideEffectAnalysisPass::hasConverged(const std::unordered_map<Function *, SideEffectInfo> &oldEffects,
+                                              const std::unordered_map<Function *, SideEffectInfo> &newEffects) const {
+  for (const auto &pair : oldEffects) {
+    Function *func = pair.first;
+    const SideEffectInfo &oldEffect = pair.second;
+
+    auto it = newEffects.find(func);
+    if (it == newEffects.end()) {
+      return false; // 函数不存在于新结果中
+    }
+
+    const SideEffectInfo &newEffect = it->second;
+
+    // 比较关键属性是否相同
+    if (oldEffect.type != newEffect.type || oldEffect.mayModifyGlobal != newEffect.mayModifyGlobal ||
+        oldEffect.mayModifyMemory != newEffect.mayModifyMemory ||
+        oldEffect.mayCallFunction != newEffect.mayCallFunction || oldEffect.isPure != newEffect.isPure) {
+      return false;
+    }
+  }
+
+  return true;
+}
+
+SideEffectInfo SysYSideEffectAnalysisPass::analyzeInstruction(Instruction *inst, Function *currentFunc,
+                                                              AnalysisManager &AM) {
+  SideEffectInfo info;
+
+  // 根据指令类型进行分析
+  if (inst->isCall()) {
+    return analyzeCallInstruction(static_cast<CallInst *>(inst), currentFunc, AM);
+  } else if (inst->isStore()) {
+    return analyzeStoreInstruction(static_cast<StoreInst *>(inst), currentFunc, AM);
+  } else if (inst->isMemset()) {
+    return analyzeMemsetInstruction(static_cast<MemsetInst *>(inst), currentFunc, AM);
+  } else if (inst->isBranch() || inst->isReturn()) {
+    // 控制流指令无副作用，但必须保留
+    info.type = SideEffectType::NO_SIDE_EFFECT;
+    info.isPure = true;
+  } else {
+    // 其他指令（算术、逻辑、比较等）通常无副作用
+    info.type = SideEffectType::NO_SIDE_EFFECT;
+    info.isPure = true;
+  }
+
+  return info;
+}
+
+SideEffectInfo SysYSideEffectAnalysisPass::analyzeCallInstruction(CallInst *call, Function *currentFunc,
+                                                                  AnalysisManager &AM) {
+  SideEffectInfo info;
+
+  // 获取被调用的函数
+  Function *calledFunc = call->getCallee();
+  if (!calledFunc) {
+    // 间接调用，保守处理
+    info.type = SideEffectType::UNKNOWN;
+    info.mayModifyGlobal = true;
+    info.mayModifyMemory = true;
+    info.mayCallFunction = true;
+    info.isPure = false;
+    return info;
+  }
+
+  std::string funcName = calledFunc->getName();
+
+  // 检查是否为已知的标准库函数
+  const SideEffectInfo *knownInfo = result->getKnownFunctionSideEffect(funcName);
+  if (knownInfo) {
+    return *knownInfo;
+  }
+
+  // 利用调用图分析结果进行精确分析
+  if (callGraphAnalysis) {
+    // 检查被调用函数是否已分析过
+    const SideEffectInfo &funcEffect = result->getFunctionSideEffect(calledFunc);
+    if (funcEffect.type != SideEffectType::NO_SIDE_EFFECT || !funcEffect.isPure) {
+      return funcEffect;
+    }
+
+    // 检查递归调用
+    if (callGraphAnalysis->isRecursive(calledFunc)) {
+      // 递归函数保守处理（在不动点算法中会精确分析）
+      info.type = SideEffectType::FUNCTION_CALL;
+      info.mayModifyGlobal = true;
+      info.mayModifyMemory = true;
+      info.mayCallFunction = true;
+      info.isPure = false;
+      return info;
+    }
+  }
+
+  // 对于未分析的用户函数，保守处理
+  info.type = SideEffectType::FUNCTION_CALL;
+  info.mayModifyGlobal = true;
+  info.mayModifyMemory = true;
+  info.mayCallFunction = true;
+  info.isPure = false;
+
+  return info;
+}
+
+SideEffectInfo SysYSideEffectAnalysisPass::analyzeStoreInstruction(StoreInst *store, Function *currentFunc,
+                                                                   AnalysisManager &AM) {
+  SideEffectInfo info;
+  info.type = SideEffectType::MEMORY_WRITE;
+  info.mayModifyMemory = true;
+  info.isPure = false;
+
+  // 获取函数的别名分析结果
+  AliasAnalysisResult *aliasAnalysis = AM.getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(currentFunc);
+  if (aliasAnalysis) {
+    Value *storePtr = store->getPointer();
+
+    // 如果存储到全局变量或可能别名的位置，则可能修改全局状态
+    if (!aliasAnalysis->isLocalArray(storePtr)) {
+      info.mayModifyGlobal = true;
+    }
+  } else {
+    // 没有别名分析结果，保守处理
+    info.mayModifyGlobal = true;
+  }
+
+  return info;
+}
+
+SideEffectInfo SysYSideEffectAnalysisPass::analyzeMemsetInstruction(MemsetInst *memset, Function *currentFunc,
+                                                                    AnalysisManager &AM) {
+  SideEffectInfo info;
+  info.type = SideEffectType::MEMORY_WRITE;
+  info.mayModifyMemory = true;
+  info.isPure = false;
+
+  // 获取函数的别名分析结果
+  AliasAnalysisResult *aliasAnalysis = AM.getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(currentFunc);
+  if (aliasAnalysis) {
+    Value *memsetPtr = memset->getPointer();
+
+    // 如果memset操作全局变量或可能别名的位置，则可能修改全局状态
+    if (!aliasAnalysis->isLocalArray(memsetPtr)) {
+      info.mayModifyGlobal = true;
+    }
+  } else {
+    // 没有别名分析结果，保守处理
+    info.mayModifyGlobal = true;
+  }
+
+  return info;
+}
+
+} // namespace sysy

src/midend/Pass/Optimize/DCE.cpp

@@ -1,9 +1,9 @@
-#include "DCE.h"            // 包含DCE遍的头文件
-#include "IR.h"             // 包含IR相关的定义
-#include "SysYIROptUtils.h" // 包含SysY IR优化工具类的定义
-#include <cassert>          // 用于断言
-#include <iostream>         // 用于调试输出
-#include <set>              // 包含set，虽然DCEContext内部用unordered_set，但这里保留
+#include "DCE.h"
+#include "SysYIROptUtils.h"
+#include "SideEffectAnalysis.h"
+#include <cassert>          
+#include <iostream>         
+#include <set>              
 
 namespace sysy {
 
@@ -17,10 +17,26 @@ void *DCE::ID = (void *)&DCE::ID;
 
 // DCEContext 的 run 方法实现
 void DCEContext::run(Function *func, AnalysisManager *AM, bool &changed) {
+  // 获取别名分析结果
+  if (AM) {
+    aliasAnalysis = AM->getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(func);
+    // 获取副作用分析结果（Module级别）
+    sideEffectAnalysis = AM->getAnalysisResult<SideEffectAnalysisResult, SysYSideEffectAnalysisPass>();
+    
+    if (DEBUG) {
+      if (aliasAnalysis) {
+        std::cout << "DCE: Using alias analysis results" << std::endl;
+      }
+      if (sideEffectAnalysis) {
+        std::cout << "DCE: Using side effect analysis results" << std::endl;
+      }
+    }
+  }
+  
   // 清空活跃指令集合，确保每次运行都是新的状态
   alive_insts.clear();
 
-  // 第一次遍历：扫描所有指令，识别“天然活跃”的指令并将其及其依赖标记为活跃
+  // 第一次遍历：扫描所有指令，识别"天然活跃"的指令并将其及其依赖标记为活跃
   // 使用 func->getBasicBlocks() 获取基本块列表，保留用户风格
   auto basicBlocks = func->getBasicBlocks();
   for (auto &basicBlock : basicBlocks) {
@@ -51,7 +67,7 @@ void DCEContext::run(Function *func, AnalysisManager *AM, bool &changed) {
       // 如果指令不在活跃集合中，则删除它。
       // 分支和返回指令由 isAlive 处理，并会被保留。
       if (alive_insts.count(currentInst) == 0) {
-        instIter =  SysYIROptUtils::usedelete(instIter); // 删除后返回下一个迭代器
+        instIter = SysYIROptUtils::usedelete(instIter); // 删除后返回下一个迭代器
         changed = true; // 标记 IR 已被修改
       } else {
         ++instIter; // 指令活跃，移动到下一个
@@ -60,20 +76,58 @@ void DCEContext::run(Function *func, AnalysisManager *AM, bool &changed) {
   }
 }
 
-// 判断指令是否是“天然活跃”的实现
+// 判断指令是否是"天然活跃"的实现
 // 只有具有副作用的指令（如存储、函数调用、原子操作）
 // 和控制流指令（如分支、返回）是天然活跃的。
 bool DCEContext::isAlive(Instruction *inst) {
-  // TODO: 后续程序并发考虑原子操作
-  // 其结果不被其他指令使用的指令（例如 StoreInst, BranchInst, ReturnInst）。
-  // dynamic_cast<ir::CallInst>(inst) 检查是否是函数调用指令，
-  // 函数调用通常有副作用。
-  // 终止指令 (BranchInst, ReturnInst) 必须是活跃的，因为它控制了程序的执行流程。
-  // 保留用户提供的 isAlive 逻辑
-  bool isBranchOrReturn = inst->isBranch() || inst->isReturn();
-  bool isCall = inst->isCall();
-  bool isStoreOrMemset = inst->isStore() || inst->isMemset(); 
-  return isBranchOrReturn || isCall || isStoreOrMemset;
+  // 终止指令 (BranchInst, ReturnInst) 必须是活跃的，因为它控制了程序的执行流程
+  if (inst->isBranch() || inst->isReturn()) {
+    return true;
+  }
+  
+  // 使用副作用分析来判断指令是否有副作用
+  if (sideEffectAnalysis && sideEffectAnalysis->hasSideEffect(inst)) {
+    return true;
+  }
+  
+  // 特殊处理Store指令：使用别名分析进行更精确的判断
+  if (inst->isStore()) {
+    auto* storeInst = static_cast<StoreInst*>(inst);
+    return mayHaveSideEffect(storeInst);
+  }
+  
+  // 特殊处理Memset指令：总是保留（因为它修改内存）
+  if (inst->isMemset()) {
+    return true;
+  }
+  
+  // 函数调用指令：总是保留（可能有未知副作用）
+  if (inst->isCall()) {
+    return true;
+  }
+  
+  // 其他指令（算术、逻辑、Load等）：无副作用，可以删除
+  return false;
+}
+
+// 检查Store指令是否可能有副作用（通过别名分析）
+bool DCEContext::mayHaveSideEffect(StoreInst* store) {
+  if (!aliasAnalysis) {
+    // 没有别名分析结果时，保守地认为所有store都有副作用
+    return true;
+  }
+  
+  Value* storePtr = store->getPointer();
+  
+  // 如果是对本地数组的存储且访问模式是常量，可能可以安全删除
+  if (aliasAnalysis->isLocalArray(storePtr)) {
+    // 检查是否有其他指令可能读取这个位置
+    // 这里需要更复杂的活性分析，暂时保守处理
+    return true; // 保守地保留所有本地数组的存储
+  }
+  
+  // 对全局变量、函数参数等的存储总是有副作用
+  return true;
 }
 
 // 递归地将活跃指令及其依赖加入到 alive_insts 集合中
@@ -102,7 +156,6 @@ void DCEContext::addAlive(Instruction *inst) {
 
 // DCE 遍的 runOnFunction 方法实现
 bool DCE::runOnFunction(Function *func, AnalysisManager &AM) {
-
   DCEContext ctx;
   bool changed = false;
   ctx.run(func, &AM, changed); // 运行 DCE 优化
@@ -120,7 +173,11 @@ bool DCE::runOnFunction(Function *func, AnalysisManager &AM) {
 
 // 声明DCE遍的分析依赖和失效信息
 void DCE::getAnalysisUsage(std::set<void *> &analysisDependencies, std::set<void *> &analysisInvalidations) const {
-  // DCE不依赖特定的分析结果，它通过遍历和副作用判断来工作。
+  // DCE依赖别名分析来更精确地判断Store指令的副作用
+  analysisDependencies.insert(&SysYAliasAnalysisPass::ID);
+  
+  // DCE依赖副作用分析来判断指令是否有副作用
+  analysisDependencies.insert(&SysYSideEffectAnalysisPass::ID);
 
   // DCE会删除指令，这会影响许多分析结果。
   // 至少，它会影响活跃性分析、支配树、控制流图（如果删除导致基本块为空并被合并）。

src/midend/Pass/Optimize/InductionVariableElimination.cpp

@@ -0,0 +1,433 @@
+#include "InductionVariableElimination.h"
+#include "LoopCharacteristics.h"
+#include "Loop.h"
+#include "Dom.h"
+#include "SideEffectAnalysis.h"
+#include "SysYIROptUtils.h"
+#include <iostream>
+#include <algorithm>
+
+// 使用全局调试开关
+extern int DEBUG;
+
+namespace sysy {
+
+// 定义 Pass 的唯一 ID
+void *InductionVariableElimination::ID = (void *)&InductionVariableElimination::ID;
+
+bool InductionVariableElimination::runOnFunction(Function* F, AnalysisManager& AM) {
+  if (F->getBasicBlocks().empty()) {
+    return false; // 空函数
+  }
+
+  if (DEBUG) {
+    std::cout << "Running InductionVariableElimination on function: " << F->getName() << std::endl;
+  }
+
+  // 创建优化上下文并运行
+  InductionVariableEliminationContext context;
+  bool modified = context.run(F, AM);
+
+  if (DEBUG) {
+    std::cout << "InductionVariableElimination " << (modified ? "modified" : "did not modify") 
+              << " function: " << F->getName() << std::endl;
+  }
+
+  return modified;
+}
+
+void InductionVariableElimination::getAnalysisUsage(std::set<void*>& analysisDependencies, 
+                                                   std::set<void*>& analysisInvalidations) const {
+  // 依赖的分析
+  analysisDependencies.insert(&LoopAnalysisPass::ID);
+  analysisDependencies.insert(&LoopCharacteristicsPass::ID);
+  analysisDependencies.insert(&DominatorTreeAnalysisPass::ID);
+  analysisDependencies.insert(&SysYSideEffectAnalysisPass::ID);
+  
+  // 会使失效的分析（归纳变量消除会修改IR结构）
+  analysisInvalidations.insert(&LoopCharacteristicsPass::ID);
+  // 注意：支配树分析通常不会因为归纳变量消除而失效，因为我们不改变控制流
+}
+
+// ========== InductionVariableEliminationContext 实现 ==========
+
+bool InductionVariableEliminationContext::run(Function* F, AnalysisManager& AM) {
+  if (DEBUG) {
+    std::cout << "  Starting induction variable elimination analysis..." << std::endl;
+  }
+
+  // 获取必要的分析结果
+  loopAnalysis = AM.getAnalysisResult<LoopAnalysisResult, LoopAnalysisPass>(F);
+  if (!loopAnalysis || !loopAnalysis->hasLoops()) {
+    if (DEBUG) {
+      std::cout << "  No loops found, skipping induction variable elimination" << std::endl;
+    }
+    return false;
+  }
+
+  loopCharacteristics = AM.getAnalysisResult<LoopCharacteristicsResult, LoopCharacteristicsPass>(F);
+  if (!loopCharacteristics) {
+    if (DEBUG) {
+      std::cout << "  LoopCharacteristics analysis not available" << std::endl;
+    }
+    return false;
+  }
+
+  dominatorTree = AM.getAnalysisResult<DominatorTree, DominatorTreeAnalysisPass>(F);
+  if (!dominatorTree) {
+    if (DEBUG) {
+      std::cout << "  DominatorTree analysis not available" << std::endl;
+    }
+    return false;
+  }
+
+  sideEffectAnalysis = AM.getAnalysisResult<SideEffectAnalysisResult, SysYSideEffectAnalysisPass>();
+  if (!sideEffectAnalysis) {
+    if (DEBUG) {
+      std::cout << "  SideEffectAnalysis not available, using conservative approach" << std::endl;
+    }
+    // 可以继续执行，但会使用更保守的策略
+  } else {
+    if (DEBUG) {
+      std::cout << "  Using SideEffectAnalysis for safety checks" << std::endl;
+    }
+  }
+
+  // 执行三个阶段的优化
+  
+  // 阶段1：识别死归纳变量
+  identifyDeadInductionVariables(F);
+  
+  if (deadIVs.empty()) {
+    if (DEBUG) {
+      std::cout << "  No dead induction variables found" << std::endl;
+    }
+    return false;
+  }
+
+  if (DEBUG) {
+    std::cout << "  Found " << deadIVs.size() << " potentially dead induction variables" << std::endl;
+  }
+
+  // 阶段2：分析安全性
+  analyzeSafetyForElimination();
+
+  // 阶段3：执行消除
+  bool modified = performInductionVariableElimination();
+
+  if (DEBUG) {
+    printDebugInfo();
+  }
+
+  return modified;
+}
+
+void InductionVariableEliminationContext::identifyDeadInductionVariables(Function* F) {
+  if (DEBUG) {
+    std::cout << "  === Phase 1: Identifying Dead Induction Variables ===" << std::endl;
+  }
+
+  // 遍历所有循环
+  for (const auto& loop_ptr : loopAnalysis->getAllLoops()) {
+    Loop* loop = loop_ptr.get();
+    
+    if (DEBUG) {
+      std::cout << "    Analyzing loop: " << loop->getName() << std::endl;
+    }
+
+    // 获取循环特征
+    const LoopCharacteristics* characteristics = loopCharacteristics->getCharacteristics(loop);
+    if (!characteristics) {
+      if (DEBUG) {
+        std::cout << "      No characteristics available for loop" << std::endl;
+      }
+      continue;
+    }
+
+    if (characteristics->InductionVars.empty()) {
+      if (DEBUG) {
+        std::cout << "      No induction variables found in loop" << std::endl;
+      }
+      continue;
+    }
+
+    // 检查每个归纳变量是否为死归纳变量
+    for (const auto& iv : characteristics->InductionVars) {
+      auto deadIV = isDeadInductionVariable(iv.get(), loop);
+      if (deadIV) {
+        if (DEBUG) {
+          std::cout << "      Found potential dead IV: %" << deadIV->phiInst->getName() << std::endl;
+        }
+        
+        // 添加到候选项列表
+        loopToDeadIVs[loop].push_back(deadIV.get());
+        deadIVs.push_back(std::move(deadIV));
+      }
+    }
+  }
+
+  if (DEBUG) {
+    std::cout << "  === End Phase 1: Found " << deadIVs.size() << " candidates ===" << std::endl;
+  }
+}
+
+std::unique_ptr<DeadInductionVariable> 
+InductionVariableEliminationContext::isDeadInductionVariable(const InductionVarInfo* iv, Loop* loop) {
+  // 获取 phi 指令
+  auto* phiInst = dynamic_cast<PhiInst*>(iv->div);
+  if (!phiInst) {
+    return nullptr; // 不是 phi 指令
+  }
+
+  // 检查是否只用于自身更新
+  if (!isUsedOnlyForSelfUpdate(phiInst, loop)) {
+    return nullptr; // 有其他用途
+  }
+
+  // 创建死归纳变量信息
+  auto deadIV = std::make_unique<DeadInductionVariable>(phiInst, loop);
+  deadIV->relatedInsts = collectRelatedInstructions(phiInst, loop);
+  
+  return deadIV;
+}
+
+bool InductionVariableEliminationContext::isUsedOnlyForSelfUpdate(PhiInst* phiInst, Loop* loop) {
+  // 检查 phi 指令的所有使用
+  for (auto use : phiInst->getUses()) {
+    auto user = use->getUser();
+    auto* userInst = dynamic_cast<Instruction*>(user);
+    
+    if (!userInst) {
+      return false; // 被非指令使用
+    }
+    
+    // 检查使用是否在循环内
+    if (!loop->contains(userInst->getParent())) {
+      return false; // 在循环外被使用
+    }
+    
+    // 检查是否为自身的更新指令
+    bool isSelfUpdate = false;
+    
+    // 检查是否为加法/减法指令（常见的归纳变量更新模式）
+    if (userInst->getKind() == Instruction::Kind::kAdd || 
+        userInst->getKind() == Instruction::Kind::kSub) {
+      auto* binInst = dynamic_cast<BinaryInst*>(userInst);
+      if (binInst && (binInst->getOperand(0) == phiInst || binInst->getOperand(1) == phiInst)) {
+        // 检查这个指令的结果是否流回到 phi
+        for (auto& [incomingBB, incomingVal] : phiInst->getIncomingValues()) {
+          if (loop->contains(incomingBB) && incomingVal == binInst) {
+            isSelfUpdate = true;
+            break;
+          }
+        }
+      }
+    }
+    
+    if (!isSelfUpdate) {
+      return false; // 有非自更新的使用
+    }
+  }
+  
+  return true; // 只用于自身更新
+}
+
+std::vector<Instruction*> InductionVariableEliminationContext::collectRelatedInstructions(
+    PhiInst* phiInst, Loop* loop) {
+  std::vector<Instruction*> relatedInsts;
+  
+  // 收集所有与该归纳变量相关的指令
+  for (auto use : phiInst->getUses()) {
+    auto user = use->getUser();
+    auto* userInst = dynamic_cast<Instruction*>(user);
+    
+    if (userInst && loop->contains(userInst->getParent())) {
+      relatedInsts.push_back(userInst);
+    }
+  }
+  
+  return relatedInsts;
+}
+
+void InductionVariableEliminationContext::analyzeSafetyForElimination() {
+  if (DEBUG) {
+    std::cout << "  === Phase 2: Analyzing Safety for Elimination ===" << std::endl;
+  }
+
+  // 为每个死归纳变量检查消除的安全性
+  for (auto& deadIV : deadIVs) {
+    bool isSafe = isSafeToEliminate(deadIV.get());
+    deadIV->canEliminate = isSafe;
+    
+    if (DEBUG) {
+      std::cout << "    Dead IV " << deadIV->phiInst->getName() 
+                << ": " << (isSafe ? "SAFE" : "UNSAFE") << " to eliminate" << std::endl;
+    }
+  }
+
+  if (DEBUG) {
+    size_t safeCount = 0;
+    for (const auto& deadIV : deadIVs) {
+      if (deadIV->canEliminate) safeCount++;
+    }
+    std::cout << "  === End Phase 2: " << safeCount << " of " << deadIVs.size() 
+              << " variables are safe to eliminate ===" << std::endl;
+  }
+}
+
+bool InductionVariableEliminationContext::isSafeToEliminate(const DeadInductionVariable* deadIV) {
+  // 1. 确保归纳变量在循环头
+  if (deadIV->phiInst->getParent() != deadIV->containingLoop->getHeader()) {
+    if (DEBUG) {
+      std::cout << "      Unsafe: phi not in loop header" << std::endl;
+    }
+    return false;
+  }
+  
+  // 2. 确保相关指令都在循环内
+  for (auto* inst : deadIV->relatedInsts) {
+    if (!deadIV->containingLoop->contains(inst->getParent())) {
+      if (DEBUG) {
+        std::cout << "      Unsafe: related instruction outside loop" << std::endl;
+      }
+      return false;
+    }
+  }
+  
+  // 3. 确保没有副作用
+  for (auto* inst : deadIV->relatedInsts) {
+    if (sideEffectAnalysis) {
+      // 使用副作用分析进行精确检查
+      if (sideEffectAnalysis->hasSideEffect(inst)) {
+        if (DEBUG) {
+          std::cout << "      Unsafe: related instruction " << inst->getName() 
+                    << " has side effects" << std::endl;
+        }
+        return false;
+      }
+    } else {
+      // 没有副作用分析时使用保守策略：只允许基本算术运算
+      auto kind = inst->getKind();
+      if (kind != Instruction::Kind::kAdd && 
+          kind != Instruction::Kind::kSub &&
+          kind != Instruction::Kind::kMul) {
+        if (DEBUG) {
+          std::cout << "      Unsafe: related instruction may have side effects (conservative)" << std::endl;
+        }
+        return false;
+      }
+    }
+  }
+  
+  // 4. 确保不影响循环的退出条件
+  for (BasicBlock* exitingBB : deadIV->containingLoop->getExitingBlocks()) {
+    auto terminatorIt = exitingBB->terminator();
+    if (terminatorIt != exitingBB->end()) {
+      Instruction* terminator = terminatorIt->get();
+      if (terminator) {
+        for (size_t i = 0; i < terminator->getNumOperands(); ++i) {
+          if (terminator->getOperand(i) == deadIV->phiInst) {
+            if (DEBUG) {
+              std::cout << "      Unsafe: phi used in loop exit condition" << std::endl;
+            }
+            return false;
+          }
+        }
+      }
+    }
+  }
+  
+  return true;
+}
+
+bool InductionVariableEliminationContext::performInductionVariableElimination() {
+  if (DEBUG) {
+    std::cout << "  === Phase 3: Performing Induction Variable Elimination ===" << std::endl;
+  }
+
+  bool modified = false;
+
+  for (auto& deadIV : deadIVs) {
+    if (!deadIV->canEliminate) {
+      continue;
+    }
+
+    if (DEBUG) {
+      std::cout << "    Eliminating dead IV: " << deadIV->phiInst->getName() << std::endl;
+    }
+
+    if (eliminateDeadInductionVariable(deadIV.get())) {
+      if (DEBUG) {
+        std::cout << "      Successfully eliminated: " << deadIV->phiInst->getName() << std::endl;
+      }
+      modified = true;
+    } else {
+      if (DEBUG) {
+        std::cout << "      Failed to eliminate: " << deadIV->phiInst->getName() << std::endl;
+      }
+    }
+  }
+
+  if (DEBUG) {
+    std::cout << "  === End Phase 3: " << (modified ? "Eliminations performed" : "No eliminations") << " ===" << std::endl;
+  }
+
+  return modified;
+}
+
+bool InductionVariableEliminationContext::eliminateDeadInductionVariable(DeadInductionVariable* deadIV) {
+  // 1. 删除所有相关指令
+  for (auto* inst : deadIV->relatedInsts) {
+    auto* bb = inst->getParent();
+    auto it = bb->findInstIterator(inst);
+    if (it != bb->end()) {
+        SysYIROptUtils::usedelete(it);
+    //   bb->getInstructions().erase(it);
+      if (DEBUG) {
+        std::cout << "        Removed related instruction: " << inst->getName() << std::endl;
+      }
+    }
+  }
+
+  // 2. 删除 phi 指令
+  auto* bb = deadIV->phiInst->getParent();
+  auto it = bb->findInstIterator(deadIV->phiInst);
+  if (it != bb->end()) {
+    SysYIROptUtils::usedelete(it);
+    // bb->getInstructions().erase(it);
+    if (DEBUG) {
+      std::cout << "        Removed phi instruction: " << deadIV->phiInst->getName() << std::endl;
+    }
+    return true;
+  }
+
+  return false;
+}
+
+void InductionVariableEliminationContext::printDebugInfo() {
+  if (!DEBUG) return;
+
+  std::cout << "\n=== Induction Variable Elimination Summary ===" << std::endl;
+  std::cout << "Total dead IVs found: " << deadIVs.size() << std::endl;
+  
+  size_t eliminatedCount = 0;
+  for (auto& [loop, loopDeadIVs] : loopToDeadIVs) {
+    size_t loopEliminatedCount = 0;
+    for (auto* deadIV : loopDeadIVs) {
+      if (deadIV->canEliminate) {
+        loopEliminatedCount++;
+        eliminatedCount++;
+      }
+    }
+    
+    if (loopEliminatedCount > 0) {
+      std::cout << "Loop " << loop->getName() << ": " << loopEliminatedCount 
+                << " of " << loopDeadIVs.size() << " IVs eliminated" << std::endl;
+    }
+  }
+  
+  std::cout << "Total eliminated: " << eliminatedCount << " of " << deadIVs.size() << std::endl;
+  std::cout << "=============================================" << std::endl;
+}
+
+} // namespace sysy

src/midend/Pass/Optimize/LICM.cpp

@@ -0,0 +1,112 @@
+#include "LICM.h"
+#include "IR.h"
+
+extern int DEBUG;
+
+namespace sysy {
+
+void *LICM::ID = (void *)&LICM::ID;
+
+bool LICMContext::run() { return hoistInstructions(); }
+
+bool LICMContext::hoistInstructions() {
+  bool changed = false;
+  BasicBlock *preheader = loop->getPreHeader();
+  if (!preheader || !chars)
+    return false;
+
+  // 1. 先收集所有可外提指令
+  std::unordered_set<Instruction *> workSet(chars->invariantInsts.begin(), chars->invariantInsts.end());
+
+  // 2. 计算每个指令被依赖的次数（入度）
+  std::unordered_map<Instruction *, int> indegree;
+  for (auto *inst : workSet) {
+    indegree[inst] = 0;
+  }
+  for (auto *inst : workSet) {
+    for (size_t i = 0; i < inst->getNumOperands(); ++i) {
+      if (auto *dep = dynamic_cast<Instruction *>(inst->getOperand(i))) {
+        if (workSet.count(dep)) {
+          indegree[inst]++;
+        }
+      }
+    }
+  }
+
+  // 3. Kahn拓扑排序
+  std::vector<Instruction *> sorted;
+  std::queue<Instruction *> q;
+  for (auto &[inst, deg] : indegree) {
+    if (deg == 0)
+      q.push(inst);
+  }
+  while (!q.empty()) {
+    auto *inst = q.front();
+    q.pop();
+    sorted.push_back(inst);
+    for (size_t i = 0; i < inst->getNumOperands(); ++i) {
+      if (auto *dep = dynamic_cast<Instruction *>(inst->getOperand(i))) {
+        if (workSet.count(dep)) {
+          indegree[dep]--;
+          if (indegree[dep] == 0)
+            q.push(dep);
+        }
+      }
+    }
+  }
+
+  // 检查是否全部排序，若未全部排序，说明有环（理论上不会）
+  if (sorted.size() != workSet.size()) {
+    if (DEBUG)
+      std::cerr << "LICM: Topological sort failed, possible dependency cycle." << std::endl;
+    return false;
+  }
+
+  // 4. 按拓扑序外提
+  for (auto *inst : sorted) {
+    if (!inst)
+      continue;
+    BasicBlock *parent = inst->getParent();
+    if (parent && loop->contains(parent)) {
+      auto sourcePos = parent->findInstIterator(inst);
+      auto targetPos = preheader->terminator();
+      parent->moveInst(sourcePos, targetPos, preheader);
+      changed = true;
+    }
+  }
+  return changed;
+}
+// ---- LICM Pass Implementation ----
+
+bool LICM::runOnFunction(Function *F, AnalysisManager &AM) {
+  auto *loopAnalysis = AM.getAnalysisResult<LoopAnalysisResult, LoopAnalysisPass>(F);
+  auto *loopCharsResult = AM.getAnalysisResult<LoopCharacteristicsResult, LoopCharacteristicsPass>(F);
+  if (!loopAnalysis || !loopCharsResult)
+    return false;
+
+  bool changed = false;
+  // 对每个函数内的所有循环做处理
+  for (const auto &loop_ptr : loopAnalysis->getAllLoops()) {
+    Loop *loop = loop_ptr.get();
+    if (DEBUG) {
+      std::cout << "LICM: Processing loop in function " << F->getName() << ": " << loop->getName() << std::endl;
+    }
+    const LoopCharacteristics *chars = loopCharsResult->getCharacteristics(loop);
+    if (!chars || !loop->getPreHeader())
+      continue; // 没有分析结果或没有前置块则跳过
+    LICMContext ctx(F, loop, builder, chars);
+    changed |= ctx.run();
+  }
+  return changed;
+}
+
+void LICM::getAnalysisUsage(std::set<void *> &analysisDependencies, std::set<void *> &analysisInvalidations) const {
+
+  analysisDependencies.insert(&LoopAnalysisPass::ID);
+  analysisDependencies.insert(&LoopCharacteristicsPass::ID);
+
+  analysisInvalidations.insert(&LoopCharacteristicsPass::ID);
+  analysisInvalidations.insert(&LivenessAnalysisPass::ID);
+}
+
+} // namespace sysy

src/midend/Pass/Optimize/LoopNormalization.cpp

@@ -0,0 +1,528 @@
+#include "LoopNormalization.h"
+#include "Dom.h"
+#include "Loop.h"
+#include "SysYIROptUtils.h"
+#include <iostream>
+#include <algorithm>
+#include <sstream>
+
+// 使用全局调试开关
+extern int DEBUG;
+
+namespace sysy {
+
+// 定义 Pass 的唯一 ID
+void *LoopNormalizationPass::ID = (void *)&LoopNormalizationPass::ID;
+
+bool LoopNormalizationPass::runOnFunction(Function *F, AnalysisManager &AM) {
+  if (F->getBasicBlocks().empty()) {
+    return false; // 空函数
+  }
+
+  if (DEBUG)
+    std::cout << "Running LoopNormalizationPass on function: " << F->getName() << std::endl;
+
+  // 获取并缓存所有需要的分析结果
+  loopAnalysis = AM.getAnalysisResult<LoopAnalysisResult, LoopAnalysisPass>(F);
+  if (!loopAnalysis || !loopAnalysis->hasLoops()) {
+    if (DEBUG)
+      std::cout << "No loops found in function " << F->getName() << ", skipping normalization" << std::endl;
+    return false; // 没有循环需要规范化
+  }
+
+  domTree = AM.getAnalysisResult<DominatorTree, DominatorTreeAnalysisPass>(F);
+  
+  if (!domTree) {
+    std::cerr << "Error: DominatorTree not available for function " << F->getName() << std::endl;
+    return false;
+  }
+
+  // 重置统计信息
+  stats = NormalizationStats();
+  
+  bool modified = false;
+  const auto& allLoops = loopAnalysis->getAllLoops();
+  stats.totalLoops = allLoops.size();
+
+  if (DEBUG) {
+    std::cout << "Found " << stats.totalLoops << " loops to analyze for normalization" << std::endl;
+  }
+
+  // 按循环深度从外到内处理，确保外层循环先规范化
+  std::vector<Loop*> sortedLoops;
+  for (const auto& loop_ptr : allLoops) {
+    sortedLoops.push_back(loop_ptr.get());
+  }
+  
+  std::sort(sortedLoops.begin(), sortedLoops.end(), [](Loop* a, Loop* b) {
+    return a->getLoopDepth() < b->getLoopDepth(); // 按深度升序排列
+  });
+
+  // 逐个规范化循环
+  for (Loop* loop : sortedLoops) {
+    if (needsPreheader(loop)) {
+      stats.loopsNeedingPreheader++;
+      
+      if (DEBUG) {
+        std::cout << "  Loop " << loop->getName() << " needs preheader (depth=" 
+                  << loop->getLoopDepth() << ")" << std::endl;
+      }
+      
+      if (normalizeLoop(loop)) {
+        modified = true;
+        stats.loopsNormalized++;
+        
+        // 验证规范化结果
+        if (!validateNormalization(loop)) {
+          std::cerr << "Warning: Loop normalization validation failed for loop " 
+                    << loop->getName() << std::endl;
+        }
+      }
+    } else {
+      if (DEBUG) {
+        auto* preheader = getExistingPreheader(loop);
+        if (preheader) {
+          std::cout << "  Loop " << loop->getName() << " already has preheader: " 
+                    << preheader->getName() << std::endl;
+        }
+      }
+    }
+  }
+
+  if (DEBUG && modified) {
+    printStats(F);
+  }
+
+  return modified;
+}
+
+bool LoopNormalizationPass::normalizeLoop(Loop* loop) {
+  if (DEBUG)
+    std::cout << "    Normalizing loop: " << loop->getName() << std::endl;
+
+  // 创建前置块
+  BasicBlock* preheader = createPreheaderForLoop(loop);
+  if (!preheader) {
+    if (DEBUG)
+      std::cout << "    Failed to create preheader for loop " << loop->getName() << std::endl;
+    return false;
+  }
+
+  stats.preheadersCreated++;
+  
+  if (DEBUG) {
+    std::cout << "    Successfully created preheader " << preheader->getName() 
+              << " for loop " << loop->getName() << std::endl;
+  }
+
+  return true;
+}
+
+BasicBlock* LoopNormalizationPass::createPreheaderForLoop(Loop* loop) {
+  BasicBlock* header = loop->getHeader();
+  if (!header) {
+    if (DEBUG)
+      std::cerr << "    Error: Loop has no header block" << std::endl;
+    return nullptr;
+  }
+
+  // 获取循环外的前驱块
+  std::vector<BasicBlock*> externalPreds = getExternalPredecessors(loop);
+  if (externalPreds.empty()) {
+    if (DEBUG)
+      std::cout << "    Loop " << loop->getName() << " has no external predecessors" << std::endl;
+    return nullptr;
+  }
+
+  if (DEBUG) {
+    std::cout << "    Found " << externalPreds.size() << " external predecessors for loop " 
+              << loop->getName() << std::endl;
+    for (auto* pred : externalPreds) {
+      std::cout << "      External pred: " << pred->getName() << std::endl;
+    }
+  }
+
+  // 生成前置块名称
+  std::string preheaderName = generatePreheaderName(loop);
+  
+  // 创建新的前置块
+  Function* parentFunction = header->getParent();
+  BasicBlock* preheader = parentFunction->addBasicBlock(preheaderName, header);
+  
+  if (!preheader) {
+    if (DEBUG)
+      std::cerr << "    Error: Failed to create basic block " << preheaderName << std::endl;
+    return nullptr;
+  }
+
+  // 在前置块中创建跳转指令到循环头部
+  builder->setPosition(preheader, preheader->end());
+  UncondBrInst* br = builder->createUncondBrInst(header);
+
+  // 更新preheader的CFG关系
+  preheader->addSuccessor(header);
+  header->addPredecessor(preheader);
+
+  if(DEBUG) {
+    std::cout << "    Created preheader " << preheader->getName() 
+              << " with unconditional branch to " << header->getName() << std::endl;
+  }
+  // 重定向外部前驱到新的前置块
+  redirectExternalPredecessors(loop, preheader, header, externalPreds);
+
+  // 更新PHI节点
+  updatePhiNodesForPreheader(header, preheader, externalPreds);
+
+  // 更新支配树关系
+  updateDominatorRelations(preheader, loop);
+
+  // 重要：更新循环对象的前置块信息
+  // 这样后续的优化遍可以通过 loop->getPreHeader() 获取到新创建的前置块
+  loop->setPreHeader(preheader);
+
+  if (DEBUG) {
+    std::cout << "    Updated loop object: preheader set to " << preheader->getName() << std::endl;
+  }
+
+  return preheader;
+}
+
+bool LoopNormalizationPass::needsPreheader(Loop* loop) {
+  // 检查是否已有合适的前置块
+  if (getExistingPreheader(loop) != nullptr) {
+    return false;
+  }
+
+  // 检查是否有外部前驱（如果没有外部前驱，不需要前置块）
+  std::vector<BasicBlock*> externalPreds = getExternalPredecessors(loop);
+  if (externalPreds.empty()) {
+    return false;
+  }
+
+  // 基于结构性需求判断：
+  // 1. 如果有多个外部前驱，必须创建前置块来合并它们
+  // 2. 如果单个外部前驱不适合作为前置块，需要创建新的前置块
+  return (externalPreds.size() > 1) || !isSuitableAsPreheader(externalPreds[0], loop);
+}
+
+BasicBlock* LoopNormalizationPass::getExistingPreheader(Loop* loop) {
+  BasicBlock* header = loop->getHeader();
+  if (!header) return nullptr;
+
+  std::vector<BasicBlock*> externalPreds = getExternalPredecessors(loop);
+  
+  // 如果只有一个外部前驱，且适合作为前置块，则返回它
+  if (externalPreds.size() == 1 && isSuitableAsPreheader(externalPreds[0], loop)) {
+    return externalPreds[0];
+  }
+
+  return nullptr;
+}
+
+void LoopNormalizationPass::updateDominatorRelations(BasicBlock* newBlock, Loop* loop) {
+  // 由于在getAnalysisUsage中声明了DominatorTree会失效，
+  // PassManager会在本遍运行后自动将支配树结果标记为失效，
+  // 后续需要支配树的Pass会触发重新计算，所以这里无需手动更新
+  
+  if (DEBUG) {
+    BasicBlock* header = loop->getHeader();
+    std::cout << "    DominatorTree marked for invalidation - new preheader " 
+              << newBlock->getName() << " will dominate " << header->getName() 
+              << " after recomputation by PassManager" << std::endl;
+  }
+}
+
+void LoopNormalizationPass::redirectExternalPredecessors(Loop* loop, BasicBlock* preheader, BasicBlock* header, 
+                                                         const std::vector<BasicBlock*>& externalPreds) {
+  // std::vector<BasicBlock*> externalPreds = getExternalPredecessors(loop);
+  
+  if (DEBUG) {
+    std::cout << "    Redirecting " << externalPreds.size() << " external predecessors" << std::endl;
+  }
+
+  for (BasicBlock* pred : externalPreds) {
+    // 获取前驱块的终止指令
+    auto termIt = pred->terminator();
+    if (termIt == pred->end()) continue;
+    
+    Instruction* terminator = termIt->get();
+    if (!terminator) continue;
+
+    // 更新跳转目标
+    if (auto* br = dynamic_cast<UncondBrInst*>(terminator)) {
+      // 无条件跳转
+      if (br->getBlock() == header) {
+        if(DEBUG){
+          std::cout << "      Updating unconditional branch from " << br->getBlock()->getName()
+                    << " to " << preheader->getName() << std::endl;
+        }
+        // 需要更新操作数
+        br->setOperand(0, preheader);
+        // 更新CFG关系
+        header->removePredecessor(pred);
+        preheader->addPredecessor(pred);
+        pred->removeSuccessor(header);
+        pred->addSuccessor(preheader);
+        
+      }
+    } else if (auto* condBr = dynamic_cast<CondBrInst*>(terminator)) {
+      // 条件跳转
+      bool updated = false;
+      if (condBr->getThenBlock() == header) {
+        condBr->setOperand(1, preheader);  // 第1个操作数是then分支
+        updated = true;
+      }
+      if (condBr->getElseBlock() == header) {
+        condBr->setOperand(2, preheader);  // 第2个操作数是else分支
+        updated = true;
+      }
+      if (updated) {
+        // 更新CFG关系
+        header->removePredecessor(pred);
+        preheader->addPredecessor(pred);
+        pred->removeSuccessor(header);
+        pred->addSuccessor(preheader);
+        
+        if (DEBUG) {
+          std::cout << "      Updated conditional branch from " << pred->getName() 
+                    << " to " << preheader->getName() << std::endl;
+        }
+      }
+    }
+  }
+}
+
+std::string LoopNormalizationPass::generatePreheaderName(Loop* loop) {
+  std::ostringstream oss;
+  oss << loop->getName() << "_preheader";
+  return oss.str();
+}
+
+bool LoopNormalizationPass::validateNormalization(Loop* loop) {
+  BasicBlock* header = loop->getHeader();
+  if (!header) return false;
+
+  // 检查循环是否现在有唯一的外部前驱
+  std::vector<BasicBlock*> externalPreds = getExternalPredecessors(loop);
+  if (externalPreds.size() != 1) {
+    if (DEBUG)
+      std::cout << "    Validation failed: Loop " << loop->getName() 
+                << " has " << externalPreds.size() << " external predecessors (expected 1)" << std::endl;
+    return false;
+  }
+
+  // 检查外部前驱是否适合作为前置块
+  BasicBlock* preheader = externalPreds[0];
+  if (!isSuitableAsPreheader(preheader, loop)) {
+    if (DEBUG)
+      std::cout << "    Validation failed: External predecessor " << preheader->getName() 
+                << " is not suitable as preheader" << std::endl;
+    return false;
+  }
+
+  // 额外验证：检查CFG连接性
+  if (!preheader->hasSuccessor(header)) {
+    if (DEBUG)
+      std::cout << "    Validation failed: Preheader " << preheader->getName() 
+                << " is not connected to header " << header->getName() << std::endl;
+    return false;
+  }
+
+  if (!header->hasPredecessor(preheader)) {
+    if (DEBUG)
+      std::cout << "    Validation failed: Header " << header->getName() 
+                << " does not have preheader " << preheader->getName() << " as predecessor" << std::endl;
+    return false;
+  }
+
+  if (DEBUG)
+    std::cout << "    Validation passed for loop " << loop->getName() << std::endl;
+  
+  return true;
+}
+
+std::vector<BasicBlock*> LoopNormalizationPass::getExternalPredecessors(Loop* loop) {
+  std::vector<BasicBlock*> externalPreds;
+  BasicBlock* header = loop->getHeader();
+  if (!header) return externalPreds;
+
+  for (BasicBlock* pred : header->getPredecessors()) {
+    if (!loop->contains(pred)) {
+      externalPreds.push_back(pred);
+    }
+  }
+
+  return externalPreds;
+}
+
+bool LoopNormalizationPass::isSuitableAsPreheader(BasicBlock* block, Loop* loop) {
+  if (!block) return false;
+
+  // 检查该块是否只有一个后继，且后继是循环头部
+  auto successors = block->getSuccessors();
+  if (successors.size() != 1) {
+    return false;
+  }
+
+  if (successors[0] != loop->getHeader()) {
+    return false;
+  }
+
+  // 检查该块是否不包含复杂的控制流
+  // 理想的前置块应该只包含简单的跳转指令
+  size_t instCount = 0;
+  for (const auto& inst : block->getInstructions()) {
+    instCount++;
+    // 如果指令过多，可能不适合作为前置块
+    if (instCount > 10) { // 阈值可调整
+      return false;
+    }
+  }
+
+  return true;
+}
+
+void LoopNormalizationPass::updatePhiNodesForPreheader(BasicBlock* header, BasicBlock* preheader,
+                                                      const std::vector<BasicBlock*>& oldPreds) {
+  if (DEBUG) {
+    std::cout << "    Updating PHI nodes in header " << header->getName() 
+              << " for new preheader " << preheader->getName() << std::endl;
+  }
+
+  std::vector<PhiInst*> phisToRemove; // 需要删除的PHI节点
+  
+  for (auto& inst : header->getInstructions()) {
+    if (auto* phi = dynamic_cast<PhiInst*>(inst.get())) {
+      if (DEBUG) {
+        std::cout << "      Processing PHI node: " << phi->getName() << std::endl;
+      }
+
+      // 收集来自外部前驱的值 - 需要保持原始的映射关系
+      std::map<BasicBlock*, Value*> externalValues;
+      for (BasicBlock* oldPred : oldPreds) {
+        Value* value = phi->getValfromBlk(oldPred);
+        if (value) {
+          externalValues[oldPred] = value;
+        }
+      }
+
+      // 处理PHI节点的更新
+      if (externalValues.size() > 1) {
+        // 多个外部前驱：在前置块中创建新的PHI节点
+        builder->setPosition(preheader, preheader->getInstructions().begin());
+        
+        std::vector<Value*> values;
+        std::vector<BasicBlock*> blocks;
+        for (auto& [block, value] : externalValues) {
+          values.push_back(value);
+          blocks.push_back(block);
+        }
+        
+        PhiInst* newPhi = builder->createPhiInst(phi->getType(), values, blocks);
+        
+        // 移除所有外部前驱的条目
+        for (BasicBlock* oldPred : oldPreds) {
+          phi->removeIncomingBlock(oldPred);
+        }
+        
+        // 添加来自新前置块的条目
+        phi->addIncoming(newPhi, preheader);
+        
+      } else if (externalValues.size() == 1) {
+        // 单个外部前驱：直接重新映射
+        Value* value = externalValues.begin()->second;
+        
+        // 移除旧的外部前驱条目
+        for (BasicBlock* oldPred : oldPreds) {
+          phi->removeIncomingBlock(oldPred);
+        }
+        
+        // 添加来自新前置块的条目
+        phi->addIncoming(value, preheader);
+        
+        // 检查PHI节点是否只剩下一个条目（只来自前置块）
+        if (phi->getNumIncomingValues() == 1) {
+          if (DEBUG) {
+            std::cout << "      PHI node " << phi->getName() 
+                      << " now has only one incoming value, scheduling for removal" << std::endl;
+          }
+          // 用单一值替换所有使用
+          Value* singleValue = phi->getIncomingValue(0u);
+          phi->replaceAllUsesWith(singleValue);
+          phisToRemove.push_back(phi);
+        }
+      } else {
+        // 没有外部值的PHI节点：检查是否需要更新
+        // 这种PHI节点只有循环内的边，通常不需要修改
+        // 但我们仍然需要检查是否只有一个条目
+        if (phi->getNumIncomingValues() == 1) {
+          if (DEBUG) {
+            std::cout << "      PHI node " << phi->getName() 
+                      << " has only one incoming value (no external), scheduling for removal" << std::endl;
+          }
+          // 用单一值替换所有使用
+          Value* singleValue = phi->getIncomingValue(0u);
+          phi->replaceAllUsesWith(singleValue);
+          phisToRemove.push_back(phi);
+        }
+      }
+      
+      if (DEBUG && std::find(phisToRemove.begin(), phisToRemove.end(), phi) == phisToRemove.end()) {
+        std::cout << "      Updated PHI node with " << externalValues.size() 
+                  << " external values, total incoming: " << phi->getNumIncomingValues() << std::endl;
+      }
+    }
+  }
+  
+  // 删除标记为移除的PHI节点
+  for (PhiInst* phi : phisToRemove) {
+    if (DEBUG) {
+      std::cout << "      Removing redundant PHI node: " << phi->getName() << std::endl;
+    }
+    SysYIROptUtils::usedelete(phi);
+  }
+  
+  // 更新统计信息
+  stats.redundantPhisRemoved += phisToRemove.size();
+  
+  if (DEBUG && !phisToRemove.empty()) {
+    std::cout << "    Removed " << phisToRemove.size() << " redundant PHI nodes" << std::endl;
+  }
+}
+
+void LoopNormalizationPass::printStats(Function* F) {
+  std::cout << "\n--- Loop Normalization Statistics for Function: " << F->getName() << " ---" << std::endl;
+  std::cout << "Total loops analyzed: " << stats.totalLoops << std::endl;
+  std::cout << "Loops needing preheader: " << stats.loopsNeedingPreheader << std::endl;
+  std::cout << "Preheaders created: " << stats.preheadersCreated << std::endl;
+  std::cout << "Loops successfully normalized: " << stats.loopsNormalized << std::endl;
+  std::cout << "Redundant PHI nodes removed: " << stats.redundantPhisRemoved << std::endl;
+  
+  if (stats.totalLoops > 0) {
+    double normalizationRate = (double)stats.loopsNormalized / stats.totalLoops * 100.0;
+    std::cout << "Normalization rate: " << normalizationRate << "%" << std::endl;
+  }
+  
+  std::cout << "---------------------------------------------------------------" << std::endl;
+}
+
+void LoopNormalizationPass::getAnalysisUsage(std::set<void *> &analysisDependencies, 
+                                            std::set<void *> &analysisInvalidations) const {
+  // LoopNormalization依赖的分析
+  analysisDependencies.insert(&LoopAnalysisPass::ID);              // 循环结构分析
+  analysisDependencies.insert(&DominatorTreeAnalysisPass::ID);     // 支配树分析
+
+  // LoopNormalization会修改CFG结构，因此会使以下分析失效
+  analysisInvalidations.insert(&DominatorTreeAnalysisPass::ID);    // 支配树需要重新计算
+  
+  // 注意：我们不让循环结构分析失效，原因如下：
+  // 1. 循环规范化只添加前置块，不改变循环的核心结构（头部、体、回边）
+  // 2. 我们会手动更新Loop对象的前置块信息（通过loop->setPreHeader()）
+  // 3. 让循环分析失效并重新计算的成本较高且不必要
+  // 4. 后续优化遍可以正确获取到更新后的前置块信息
+  // 
+  // 如果未来有更复杂的循环结构修改，可能需要考虑让循环分析失效：
+  // analysisInvalidations.insert(&LoopAnalysisPass::ID);
+}
+
+} // namespace sysy

src/midend/Pass/Optimize/Mem2Reg.cpp

@@ -1,6 +1,8 @@
 #include "Mem2Reg.h" // 包含 Mem2Reg 遍的头文件
 #include "Dom.h"     // 包含支配树分析的头文件
 #include "Liveness.h"
+#include "AliasAnalysis.h" // 包含别名分析
+#include "SideEffectAnalysis.h" // 包含副作用分析
 #include "IR.h"      // 包含 IR 相关的定义
 #include "SysYIROptUtils.h"
 #include <cassert>   // 用于断言
@@ -420,8 +422,9 @@ void Mem2Reg::getAnalysisUsage(std::set<void *> &analysisDependencies, std::set<
   // 因此，它会使许多分析结果失效。
   analysisInvalidations.insert(&DominatorTreeAnalysisPass::ID); // 支配树可能受影响
   analysisInvalidations.insert(&LivenessAnalysisPass::ID); // 活跃性分析肯定失效
+  analysisInvalidations.insert(&SysYAliasAnalysisPass::ID); // 别名分析必须失效，因为Mem2Reg改变了内存访问模式
+  analysisInvalidations.insert(&SysYSideEffectAnalysisPass::ID); // 副作用分析也可能失效
   // analysisInvalidations.insert(&LoopInfoAnalysisPass::ID); // 循环信息可能失效
-  // analysisInvalidations.insert(&SideEffectInfoAnalysisPass::ID); // 副作用分析可能失效
   // 其他所有依赖于数据流或 IR 结构的分析都可能失效。
 }
 

src/midend/Pass/Optimize/SCCP.cpp

@@ -1,10 +1,12 @@
 #include "SCCP.h"
 #include "Dom.h"
 #include "Liveness.h"
+#include "SideEffectAnalysis.h"
 #include <algorithm>
 #include <cassert>
 #include <cmath>  // For std::fmod, std::fabs
 #include <limits> // For std::numeric_limits
+#include <set>    // For std::set in isKnownPureFunction
 
 namespace sysy {
 
@@ -263,6 +265,192 @@ SSAPValue SCCPContext::ComputeConstant(UnaryInst *unaryInst, SSAPValue operandVa
   return SSAPValue(LatticeVal::Bottom);
 }
 
+// 辅助函数：检查是否为已知的纯函数
+bool SCCPContext::isKnownPureFunction(const std::string &funcName) const {
+  // SysY中一些已知的纯函数（不修改全局状态，结果只依赖参数）
+  static const std::set<std::string> knownPureFunctions = {
+    // 数学函数（如果有的话）
+    // "abs", "fabs", "sqrt", "sin", "cos"
+    // SysY标准中基本没有纯函数，大多数都有I/O副作用
+  };
+  
+  return knownPureFunctions.find(funcName) != knownPureFunctions.end();
+}
+
+// 辅助函数：计算纯函数的常量结果
+SSAPValue SCCPContext::computePureFunctionResult(CallInst *call, const std::vector<SSAPValue> &argValues) {
+  Function *calledFunc = call->getCallee();
+  if (!calledFunc) {
+    return SSAPValue(LatticeVal::Bottom);
+  }
+  
+  std::string funcName = calledFunc->getName();
+  
+  // 目前SysY中没有标准的纯函数，这里预留扩展空间
+  // 未来可以添加数学函数的常量折叠
+  /*
+  if (funcName == "abs" && argValues.size() == 1) {
+    if (argValues[0].constant_type == ValueType::Integer) {
+      int val = std::get<int>(argValues[0].constantVal);
+      return SSAPValue(std::abs(val));
+    }
+  }
+  */
+  
+  return SSAPValue(LatticeVal::Bottom);
+}
+
+// 辅助函数：查找存储到指定位置的常量值
+SSAPValue SCCPContext::findStoredConstantValue(Value *ptr, BasicBlock *currentBB) {
+  if (!aliasAnalysis) {
+    if (DEBUG) {
+      std::cout << "SCCP: No alias analysis available" << std::endl;
+    }
+    return SSAPValue(LatticeVal::Bottom);
+  }
+  
+  if (DEBUG) {
+    std::cout << "SCCP: Searching for stored constant value for ptr" << std::endl;
+  }
+  
+  // 从当前块的指令列表末尾向前查找最近的Store
+  std::vector<Instruction*> instructions;
+  for (auto it = currentBB->begin(); it != currentBB->end(); ++it) {
+    instructions.push_back(it->get());
+  }
+  
+  for (int i = instructions.size() - 1; i >= 0; --i) {
+    Instruction *prevInst = instructions[i];
+    
+    if (prevInst->isStore()) {
+      StoreInst *storeInst = static_cast<StoreInst *>(prevInst);
+      Value *storePtr = storeInst->getPointer();
+      
+      if (DEBUG) {
+        std::cout << "SCCP: Checking store instruction" << std::endl;
+      }
+      
+      // 使用别名分析检查Store是否针对相同的内存位置
+      auto aliasResult = aliasAnalysis->queryAlias(ptr, storePtr);
+      
+      if (DEBUG) {
+        std::cout << "SCCP: Alias result: " << (int)aliasResult << std::endl;
+      }
+      
+      if (aliasResult == AliasType::SELF_ALIAS) {
+        // 找到了对相同位置的Store，获取存储的值
+        Value *storedValue = storeInst->getValue();
+        
+        if (DEBUG) {
+          std::cout << "SCCP: Found matching store, checking value type" << std::endl;
+        }
+        
+        // 检查存储的值是否为常量
+        if (auto constInt = dynamic_cast<ConstantInteger *>(storedValue)) {
+          int val = std::get<int>(constInt->getVal());
+          if (DEBUG) {
+            std::cout << "SCCP: Found constant integer value: " << val << std::endl;
+          }
+          return SSAPValue(val);
+        } else if (auto constFloat = dynamic_cast<ConstantFloating *>(storedValue)) {
+          float val = std::get<float>(constFloat->getVal());
+          if (DEBUG) {
+            std::cout << "SCCP: Found constant float value: " << val << std::endl;
+          }
+          return SSAPValue(val);
+        } else {
+          // 存储的值不是常量，检查其SCCP状态
+          SSAPValue storedState = GetValueState(storedValue);
+          if (storedState.state == LatticeVal::Constant) {
+            if (DEBUG) {
+              std::cout << "SCCP: Found SCCP constant value" << std::endl;
+            }
+            return storedState;
+          } else {
+            if (DEBUG) {
+              std::cout << "SCCP: Stored value is not constant" << std::endl;
+            }
+          }
+        }
+        
+        // 找到了最近的Store但不是常量，停止查找
+        if (DEBUG) {
+          std::cout << "SCCP: Found non-constant store, stopping search" << std::endl;
+        }
+        break;
+      }
+    }
+  }
+  
+  if (DEBUG) {
+    std::cout << "SCCP: No constant value found" << std::endl;
+  }
+  return SSAPValue(LatticeVal::Bottom);
+}
+
+// 辅助函数：动态检查数组访问是否为常量索引（考虑SCCP状态）
+bool SCCPContext::hasRuntimeConstantAccess(Value *ptr) {
+  if (auto gep = dynamic_cast<GetElementPtrInst *>(ptr)) {
+    if (DEBUG) {
+      std::cout << "SCCP: Checking runtime constant access for GEP instruction" << std::endl;
+    }
+    
+    // 检查所有索引是否为常量或SCCP传播的常量
+    bool allConstantIndices = true;
+    for (auto indexUse : gep->getIndices()) {
+      Value* index = indexUse->getValue();
+      
+      // 首先检查是否为编译时常量
+      if (auto constInt = dynamic_cast<ConstantInteger *>(index)) {
+        if (DEBUG) {
+          std::cout << "SCCP: Index is compile-time constant integer: " << std::get<int>(constInt->getVal()) << std::endl;
+        }
+        continue;
+      }
+      if (auto constFloat = dynamic_cast<ConstantFloating *>(index)) {
+        if (DEBUG) {
+          std::cout << "SCCP: Index is compile-time constant float: " << std::get<float>(constFloat->getVal()) << std::endl;
+        }
+        continue;
+      }
+      
+      // 检查是否为SCCP传播的常量
+      SSAPValue indexState = GetValueState(index);
+      if (indexState.state == LatticeVal::Constant) {
+        if (DEBUG) {
+          std::cout << "SCCP: Index is SCCP constant: ";
+          if (indexState.constant_type == ValueType::Integer) {
+            std::cout << std::get<int>(indexState.constantVal);
+          } else {
+            std::cout << std::get<float>(indexState.constantVal);
+          }
+          std::cout << std::endl;
+        }
+        continue;
+      }
+      
+      // 如果任何一个索引不是常量，返回false
+      if (DEBUG) {
+        std::cout << "SCCP: Index is not constant, access is not constant" << std::endl;
+      }
+      allConstantIndices = false;
+      break;
+    }
+    
+    if (DEBUG) {
+      std::cout << "SCCP: hasRuntimeConstantAccess result: " << (allConstantIndices ? "true" : "false") << std::endl;
+    }
+    return allConstantIndices;
+  }
+  
+  // 对于非GEP指令，回退到别名分析的静态结果
+  if (aliasAnalysis) {
+    return aliasAnalysis->hasConstantAccess(ptr);
+  }
+  
+  return false;
+}
+
 // 辅助函数：处理单条指令
 void SCCPContext::ProcessInstruction(Instruction *inst) {
   SSAPValue oldState = GetValueState(inst);
@@ -396,28 +584,237 @@ void SCCPContext::ProcessInstruction(Instruction *inst) {
     break;
   }
   case Instruction::kLoad: {
-    // 对于 Load 指令，除非我们有特殊的别名分析，否则假定为 Bottom
-    // 或者如果它加载的是一个已知常量地址的全局常量
+    // 使用别名分析和副作用分析改进Load指令的处理
     Value *ptr = inst->getOperand(0);
+    
+    // 首先检查是否是全局常量
     if (auto globalVal = dynamic_cast<GlobalValue *>(ptr)) {
       // 如果 GlobalValue 有初始化器，并且它是常量，我们可以传播
-      // 这需要额外的逻辑来检查 globalVal 的初始化器
-      // 暂时保守地设置为 Bottom
+      // TODO: 检查全局变量的初始化器进行常量传播
       newState = SSAPValue(LatticeVal::Bottom);
+    } else if (aliasAnalysis && sideEffectAnalysis) {
+      // 使用别名分析和副作用分析进行更精确的Load分析
+      if (aliasAnalysis->isLocalArray(ptr) && (aliasAnalysis->hasConstantAccess(ptr) || hasRuntimeConstantAccess(ptr))) {
+        // 对于局部数组的常量索引访问，检查是否有影响该位置的Store
+        bool mayBeModified = false;
+        
+        if (DEBUG) {
+          std::cout << "SCCP: Analyzing local array with constant access for modification" << std::endl;
+        }
+        
+        // 遍历指令所在块之前的所有指令，查找可能修改该内存位置的Store
+        BasicBlock *currentBB = inst->getParent();
+        auto instPos = currentBB->findInstIterator(inst);
+        
+        SSAPValue foundConstantValue = SSAPValue(LatticeVal::Bottom);
+        bool hasFoundDefinitiveStore = false;
+        
+        for (auto it = currentBB->begin(); it != instPos; ++it) {
+          Instruction *prevInst = it->get();
+          
+          if (prevInst->isStore()) {
+            StoreInst *storeInst = static_cast<StoreInst *>(prevInst);
+            Value *storePtr = storeInst->getPointer();
+            
+            // 使用别名分析判断Store是否可能影响当前Load
+            auto aliasResult = aliasAnalysis->queryAlias(ptr, storePtr);
+            if (DEBUG) {
+              std::cout << "SCCP: Checking store with alias result: " << (int)aliasResult << std::endl;
+            }
+            
+            if (aliasResult == AliasType::SELF_ALIAS) {
+              // 找到对相同位置的精确Store
+              Value *storedValue = storeInst->getValue();
+              
+              if (DEBUG) {
+                std::cout << "SCCP: Found exact store to same location, checking value" << std::endl;
+              }
+              
+              // 检查存储的值是否为常量
+              if (auto constInt = dynamic_cast<ConstantInteger *>(storedValue)) {
+                int val = std::get<int>(constInt->getVal());
+                if (DEBUG) {
+                  std::cout << "SCCP: Store contains constant integer: " << val << std::endl;
+                }
+                foundConstantValue = SSAPValue(val);
+                hasFoundDefinitiveStore = true;
+                // 继续遍历，查找是否有更后面的Store覆盖这个值
+              } else if (auto constFloat = dynamic_cast<ConstantFloating *>(storedValue)) {
+                float val = std::get<float>(constFloat->getVal());
+                if (DEBUG) {
+                  std::cout << "SCCP: Store contains constant float: " << val << std::endl;
+                }
+                foundConstantValue = SSAPValue(val);
+                hasFoundDefinitiveStore = true;
+              } else {
+                // 存储的值不是编译时常量，检查其SCCP状态
+                SSAPValue storedState = GetValueState(storedValue);
+                if (storedState.state == LatticeVal::Constant) {
+                  if (DEBUG) {
+                    std::cout << "SCCP: Store contains SCCP constant" << std::endl;
+                  }
+                  foundConstantValue = storedState;
+                  hasFoundDefinitiveStore = true;
+                } else {
+                  if (DEBUG) {
+                    std::cout << "SCCP: Store contains non-constant value" << std::endl;
+                  }
+                  // 非常量Store覆盖了之前的常量，无法传播
+                  foundConstantValue = SSAPValue(LatticeVal::Bottom);
+                  hasFoundDefinitiveStore = true;
+                }
+              }
+            } else if (aliasResult != AliasType::NO_ALIAS) {
+              // 可能有别名，但不确定
+              if (DEBUG) {
+                std::cout << "SCCP: Found store with uncertain alias, stopping propagation" << std::endl;
+              }
+              mayBeModified = true;
+              break;
+            }
+          } else if (prevInst->isCall()) {
+            // 检查函数调用是否可能修改该内存位置
+            if (sideEffectAnalysis->mayModifyMemory(prevInst)) {
+              // 进一步检查是否可能影响局部数组
+              if (!aliasAnalysis->isLocalArray(ptr) || 
+                  sideEffectAnalysis->mayModifyGlobal(prevInst)) {
+                mayBeModified = true;
+                break;
+              }
+            }
+          } else if (prevInst->isMemset()) {
+            // Memset指令可能影响内存，但只有在它在相关Store之前时才阻止常量传播
+            MemsetInst *memsetInst = static_cast<MemsetInst *>(prevInst);
+            Value *memsetPtr = memsetInst->getOperand(0);
+            
+            auto aliasResult = aliasAnalysis->queryAlias(ptr, memsetPtr);
+            if (aliasResult != AliasType::NO_ALIAS) {
+              // Memset可能影响这个位置，但我们继续查找是否有Store覆盖了memset
+              // 不立即设置mayBeModified = true，让后续的Store有机会覆盖
+              if (DEBUG) {
+                std::cout << "SCCP: Found memset that may affect location, but continuing to check for overwriting stores" << std::endl;
+              }
+            }
+          }
+        }
+        
+        if (DEBUG) {
+          std::cout << "SCCP: mayBeModified = " << (mayBeModified ? "true" : "false") << std::endl;
+          std::cout << "SCCP: hasFoundDefinitiveStore = " << (hasFoundDefinitiveStore ? "true" : "false") << std::endl;
+        }
+        
+        if (!mayBeModified) {
+          if (hasFoundDefinitiveStore && foundConstantValue.state == LatticeVal::Constant) {
+            // 直接使用找到的常量值
+            if (DEBUG) {
+              std::cout << "SCCP: Using found constant value from store analysis: ";
+              if (foundConstantValue.constant_type == ValueType::Integer) {
+                std::cout << std::get<int>(foundConstantValue.constantVal);
+              } else {
+                std::cout << std::get<float>(foundConstantValue.constantVal);
+              }
+              std::cout << std::endl;
+            }
+            newState = foundConstantValue;
+          } else {
+            // 如果没有发现修改该位置的指令，尝试用旧方法找到对应的Store值
+            SSAPValue constantValue = findStoredConstantValue(ptr, inst->getParent());
+            if (constantValue.state == LatticeVal::Constant) {
+              if (DEBUG) {
+                std::cout << "SCCP: Found constant value for array load using fallback method: ";
+                if (constantValue.constant_type == ValueType::Integer) {
+                  std::cout << std::get<int>(constantValue.constantVal);
+                } else {
+                  std::cout << std::get<float>(constantValue.constantVal);
+                }
+                std::cout << std::endl;
+              }
+              newState = constantValue;
+            } else {
+              newState = SSAPValue(LatticeVal::Bottom);
+            }
+          }
+        } else {
+          newState = SSAPValue(LatticeVal::Bottom);
+        }
+      } else {
+        // 非局部数组或非常量访问，保守处理
+        newState = SSAPValue(LatticeVal::Bottom);
+      }
     } else {
+      // 没有分析信息时保守处理
       newState = SSAPValue(LatticeVal::Bottom);
     }
+    
+    if (DEBUG && aliasAnalysis && sideEffectAnalysis) {
+      std::cout << "SCCP: Load instruction analysis - " 
+                << (aliasAnalysis->isLocalArray(ptr) ? "local array" : "other")
+                << ", static constant access: " 
+                << (aliasAnalysis->hasConstantAccess(ptr) ? "yes" : "no")
+                << ", runtime constant access: "
+                << (hasRuntimeConstantAccess(ptr) ? "yes" : "no") << std::endl;
+    }
     break;
   }
   case Instruction::kStore:
     // Store 指令不产生值，其 SSAPValue 不重要
     newState = SSAPValue(); // 保持 Top
     break;
-  case Instruction::kCall:
-    // TODO: 处理 Call 指令根据副作用分析可以推断的常量
-    // 大多数 Call 指令都假定为 Bottom，除非是纯函数且所有参数都是常量
-    newState = SSAPValue(LatticeVal::Bottom);
+  case Instruction::kCall: {
+    // 使用副作用分析改进Call指令处理
+    CallInst *callInst = static_cast<CallInst *>(inst);
+    
+    if (sideEffectAnalysis) {
+      const auto &sideEffect = sideEffectAnalysis->getInstructionSideEffect(callInst);
+      
+      // 检查是否为纯函数且所有参数都是常量
+      if (sideEffect.isPure && sideEffect.type == SideEffectType::NO_SIDE_EFFECT) {
+        // 对于纯函数，检查所有参数是否都是常量
+        bool allArgsConstant = true;
+        std::vector<SSAPValue> argValues;
+        
+        for (unsigned i = 0; i < callInst->getNumOperands() - 1; ++i) { // 减1排除函数本身
+          SSAPValue argVal = GetValueState(callInst->getOperand(i));
+          argValues.push_back(argVal);
+          if (argVal.state != LatticeVal::Constant) {
+            allArgsConstant = false;
+            break;
+          }
+        }
+        
+        if (allArgsConstant) {
+          // 对于参数全为常量的纯函数，可以尝试常量折叠
+          // 但由于实际执行函数比较复杂，这里先标记为可优化
+          // TODO: 实现具体的纯函数常量折叠
+          Function *calledFunc = callInst->getCallee();
+          if (calledFunc && isKnownPureFunction(calledFunc->getName())) {
+            // 对已知的纯函数进行常量计算
+            newState = computePureFunctionResult(callInst, argValues);
+          } else {
+            newState = SSAPValue(LatticeVal::Bottom);
+          }
+        } else {
+          // 参数不全是常量，但函数无副作用
+          newState = SSAPValue(LatticeVal::Bottom);
+        }
+        
+        if (DEBUG) {
+          std::cout << "SCCP: Pure function call with " 
+                    << (allArgsConstant ? "constant" : "non-constant") << " arguments" << std::endl;
+        }
+      } else {
+        // 有副作用的函数调用，保守处理
+        newState = SSAPValue(LatticeVal::Bottom);
+        if (DEBUG) {
+          std::cout << "SCCP: Function call with side effects" << std::endl;
+        }
+      }
+    } else {
+      // 没有副作用分析时，保守处理所有Call
+      newState = SSAPValue(LatticeVal::Bottom);
+    }
     break;
+  }
   case Instruction::kGetElementPtr: {
     // GEP 指令计算地址，通常其结果值（地址指向的内容）是 Bottom
     // 除非所有索引和基指针都是常量，指向一个确定常量值的内存位置
@@ -970,12 +1367,34 @@ bool SCCP::runOnFunction(Function *F, AnalysisManager &AM) {
   if (DEBUG) {
     std::cout << "Running SCCP on function: " << F->getName() << std::endl;
   }
+  
   SCCPContext context(builder);
+  
+  // 获取别名分析结果
+  if (auto *aliasResult = AM.getAnalysisResult<AliasAnalysisResult, SysYAliasAnalysisPass>(F)) {
+    context.setAliasAnalysis(aliasResult);
+    if (DEBUG) {
+      std::cout << "SCCP: Using alias analysis results" << std::endl;
+    }
+  }
+  
+  // 获取副作用分析结果（Module级别）
+  if (auto *sideEffectResult = AM.getAnalysisResult<SideEffectAnalysisResult, SysYSideEffectAnalysisPass>()) {
+    context.setSideEffectAnalysis(sideEffectResult);
+    if (DEBUG) {
+      std::cout << "SCCP: Using side effect analysis results" << std::endl;
+    }
+  }
+  
   context.run(F, AM);
   return true;
 }
 
 void SCCP::getAnalysisUsage(std::set<void *> &analysisDependencies, std::set<void *> &analysisInvalidations) const {
+  // 声明依赖别名分析和副作用分析
+  analysisDependencies.insert(&SysYAliasAnalysisPass::ID);
+  analysisDependencies.insert(&SysYSideEffectAnalysisPass::ID);
+  
   // analysisInvalidations.insert(nullptr); // 表示使所有默认分析失效
   analysisInvalidations.insert(&DominatorTreeAnalysisPass::ID); // 支配树可能受影响
   analysisInvalidations.insert(&LivenessAnalysisPass::ID); // 活跃性分析很可能失效

src/midend/Pass/Pass.cpp

@@ -1,5 +1,10 @@
 #include "Dom.h"
 #include "Liveness.h"
+#include "Loop.h"
+#include "LoopCharacteristics.h"
+#include "AliasAnalysis.h"
+#include "CallGraphAnalysis.h"
+#include "SideEffectAnalysis.h"
 #include "SysYIRCFGOpt.h"
 #include "SysYIRPrinter.h"
 #include "DCE.h"
@@ -8,6 +13,10 @@
 #include "SCCP.h"
 #include "BuildCFG.h"
 #include "LargeArrayToGlobal.h"
+#include "LoopNormalization.h"
+#include "LICM.h"
+#include "LoopStrengthReduction.h"
+#include "InductionVariableElimination.h"
 #include "Pass.h"
 #include <iostream>
 #include <queue>
@@ -39,6 +48,13 @@ void PassManager::runOptimizationPipeline(Module* moduleIR, IRBuilder* builderIR
     // 注册分析遍
     registerAnalysisPass<DominatorTreeAnalysisPass>();
     registerAnalysisPass<LivenessAnalysisPass>();
+    registerAnalysisPass<sysy::DominatorTreeAnalysisPass>();
+    registerAnalysisPass<sysy::LivenessAnalysisPass>();
+    registerAnalysisPass<SysYAliasAnalysisPass>();           // 别名分析 (优先级高)
+    registerAnalysisPass<CallGraphAnalysisPass>();           // 调用图分析 (Module级别，独立分析)
+    registerAnalysisPass<SysYSideEffectAnalysisPass>();      // 副作用分析 (依赖别名分析和调用图)
+    registerAnalysisPass<LoopAnalysisPass>();
+    registerAnalysisPass<LoopCharacteristicsPass>();        // 循环特征分析依赖别名分析
 
     // 注册优化遍
     registerOptimizationPass<BuildCFG>();
@@ -54,6 +70,10 @@ void PassManager::runOptimizationPipeline(Module* moduleIR, IRBuilder* builderIR
 
     registerOptimizationPass<DCE>();
     registerOptimizationPass<Mem2Reg>(builderIR);
+    registerOptimizationPass<LoopNormalizationPass>(builderIR);
+    registerOptimizationPass<LICM>(builderIR);
+    registerOptimizationPass<LoopStrengthReduction>(builderIR);
+    registerOptimizationPass<InductionVariableElimination>();
     registerOptimizationPass<Reg2Mem>(builderIR);
 
     registerOptimizationPass<SCCP>(builderIR);
@@ -119,9 +139,21 @@ void PassManager::runOptimizationPipeline(Module* moduleIR, IRBuilder* builderIR
       }
 
       this->clearPasses();
-      this->addPass(&Reg2Mem::ID);
+      this->addPass(&LoopNormalizationPass::ID);
+      this->addPass(&LICM::ID);
+      this->addPass(&LoopStrengthReduction::ID);
+      this->addPass(&InductionVariableElimination::ID);
       this->run();
 
+      if(DEBUG) {
+        std::cout << "=== IR After Loop Normalization, LICM, and Strength Reduction Optimizations ===\n";
+        printPasses();
+      }
+
+      // this->clearPasses();
+      // this->addPass(&Reg2Mem::ID);
+      // this->run();
+
       if(DEBUG) {
         std::cout << "=== IR After Reg2Mem Optimizations ===\n";
         printPasses();

src/midend/SysYIRPrinter.cpp

@@ -240,7 +240,9 @@ void SysYPrinter::printInst(Instruction *pInst) {
     case Kind::kMul:
     case Kind::kDiv:
     case Kind::kRem:
-    case Kind::kSRA:
+    case Kind::kSrl:
+    case Kind::kSll:
+    case Kind::kSra:
     case Kind::kMulh:
     case Kind::kFAdd:
     case Kind::kFSub:
@@ -274,7 +276,9 @@ void SysYPrinter::printInst(Instruction *pInst) {
         case Kind::kMul: std::cout << "mul"; break;
         case Kind::kDiv: std::cout << "sdiv"; break;
         case Kind::kRem: std::cout << "srem"; break;
-        case Kind::kSRA: std::cout << "ashr"; break;
+        case Kind::kSrl: std::cout << "lshr"; break;
+        case Kind::kSll: std::cout << "shl"; break;
+        case Kind::kSra: std::cout << "ashr"; break;
         case Kind::kMulh: std::cout << "mulh"; break;
         case Kind::kFAdd: std::cout << "fadd"; break;
         case Kind::kFSub: std::cout << "fsub"; break;

src/sysyc.cpp

@@ -35,7 +35,7 @@ void usage(int code) {
                     "Supported options:\n"
                     "  -h \tprint help message and exit\n"
                     "  -f \tpretty-format the input file\n"
-                    "  -s {ast,ir,asm,llvmir,asmd,ird}\tstop after generating AST/IR/Assembly\n"
+                    "  -s {ast,ir,asm,asmd,ird}\tstop after generating AST/IR/Assembly\n"
                     "  -S \tcompile to assembly (.s file)\n"
                     "  -o <file>\tplace the output into <file>\n"
                     "  -O<level>\tenable optimization at <level> (e.g., -O0, -O1)\n";