├── images
    └── hitTest.jpg
├── KICachePolicy.h
├── CMakeLists.txt
├── KArcCache
    ├── KArcCacheNode.h
    ├── KArcCache.h
    ├── KArcLruPart.h
    └── KArcLfuPart.h
├── .vscode
    └── settings.json
├── README.md
├── KLruCache.h
├── KLfuCache.h
├── testAllCachePolicy.cpp
└── LICENSE


/images/hitTest.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/youngyangyang04/KamaCache/HEAD/images/hitTest.jpg


--------------------------------------------------------------------------------
/KICachePolicy.h:
--------------------------------------------------------------------------------
 1 | #pragma once
 2 | 
 3 | namespace KamaCache
 4 | {
 5 | 
 6 | template <typename Key, typename Value>
 7 | class KICachePolicy
 8 | {
 9 | public:
10 |     virtual ~KICachePolicy() {};
11 | 
12 |     // 添加缓存接口
13 |     virtual void put(Key key, Value value) = 0;
14 | 
15 |     // key是传入参数  访问到的值以传出参数的形式返回 | 访问成功返回true
16 |     virtual bool get(Key key, Value& value) = 0;
17 |     // 如果缓存中能找到key，则直接返回value
18 |     virtual Value get(Key key) = 0;
19 | 
20 | };
21 | 
22 | } // namespace KamaCache


--------------------------------------------------------------------------------
/CMakeLists.txt:
--------------------------------------------------------------------------------
 1 | # 设置最低 CMake 版本要求
 2 | cmake_minimum_required(VERSION 3.10)
 3 | 
 4 | # 设置项目名称
 5 | project(KCacheSystem)
 6 | 
 7 | # 设置 C++ 标准
 8 | set(CMAKE_CXX_STANDARD 17)
 9 | set(CMAKE_CXX_STANDARD_REQUIRED True)
10 | 
11 | # 指定源文件目录下的所有 .cpp 文件
12 | file(GLOB SOURCES "*.cpp")
13 | 
14 | # 设置目标可执行文件
15 | add_executable(main ${SOURCES})
16 | 
17 | # 清理中间的 .o 文件
18 | set_target_properties(main PROPERTIES CLEAN_DIRECT_OUTPUT 1)
19 | 
20 | # 额外的编译选项（可根据需要启用）
21 | # target_compile_options(main PRIVATE -Wall -Wextra -O2)


--------------------------------------------------------------------------------
/KArcCache/KArcCacheNode.h:
--------------------------------------------------------------------------------
 1 | #pragma once
 2 | 
 3 | #include <memory>
 4 | 
 5 | namespace KamaCache 
 6 | {
 7 | 
 8 | template<typename Key, typename Value>
 9 | class ArcNode 
10 | {
11 | private:
12 |     Key key_;
13 |     Value value_;
14 |     size_t accessCount_;
15 |     std::weak_ptr<ArcNode> prev_;
16 |     std::shared_ptr<ArcNode> next_;
17 | 
18 | public:
19 |     ArcNode() : accessCount_(1), next_(nullptr) {}
20 |     
21 |     ArcNode(Key key, Value value) 
22 |         : key_(key)
23 |         , value_(value)
24 |         , accessCount_(1)
25 |         , next_(nullptr) 
26 |     {}
27 | 
28 |     // Getters
29 |     Key getKey() const { return key_; }
30 |     Value getValue() const { return value_; }
31 |     size_t getAccessCount() const { return accessCount_; }
32 |     
33 |     // Setters
34 |     void setValue(const Value& value) { value_ = value; }
35 |     void incrementAccessCount() { ++accessCount_; }
36 | 
37 |     template<typename K, typename V> friend class ArcLruPart;
38 |     template<typename K, typename V> friend class ArcLfuPart;
39 | };
40 | 
41 | } // namespace KamaCache


--------------------------------------------------------------------------------
/.vscode/settings.json:
--------------------------------------------------------------------------------
 1 | {
 2 |     "files.associations": {
 3 |         "thread": "cpp",
 4 |         "cctype": "cpp",
 5 |         "clocale": "cpp",
 6 |         "cmath": "cpp",
 7 |         "cstdarg": "cpp",
 8 |         "cstddef": "cpp",
 9 |         "cstdio": "cpp",
10 |         "cstdlib": "cpp",
11 |         "cstring": "cpp",
12 |         "ctime": "cpp",
13 |         "cwchar": "cpp",
14 |         "cwctype": "cpp",
15 |         "array": "cpp",
16 |         "atomic": "cpp",
17 |         "*.tcc": "cpp",
18 |         "chrono": "cpp",
19 |         "condition_variable": "cpp",
20 |         "cstdint": "cpp",
21 |         "deque": "cpp",
22 |         "list": "cpp",
23 |         "unordered_map": "cpp",
24 |         "vector": "cpp",
25 |         "exception": "cpp",
26 |         "algorithm": "cpp",
27 |         "functional": "cpp",
28 |         "iterator": "cpp",
29 |         "map": "cpp",
30 |         "memory": "cpp",
31 |         "memory_resource": "cpp",
32 |         "numeric": "cpp",
33 |         "optional": "cpp",
34 |         "random": "cpp",
35 |         "ratio": "cpp",
36 |         "string": "cpp",
37 |         "string_view": "cpp",
38 |         "system_error": "cpp",
39 |         "tuple": "cpp",
40 |         "type_traits": "cpp",
41 |         "utility": "cpp",
42 |         "fstream": "cpp",
43 |         "initializer_list": "cpp",
44 |         "iomanip": "cpp",
45 |         "iosfwd": "cpp",
46 |         "iostream": "cpp",
47 |         "istream": "cpp",
48 |         "limits": "cpp",
49 |         "mutex": "cpp",
50 |         "new": "cpp",
51 |         "ostream": "cpp",
52 |         "sstream": "cpp",
53 |         "stdexcept": "cpp",
54 |         "streambuf": "cpp",
55 |         "cinttypes": "cpp",
56 |         "typeinfo": "cpp"
57 |     }
58 | }


--------------------------------------------------------------------------------
/KArcCache/KArcCache.h:
--------------------------------------------------------------------------------
 1 | #pragma once
 2 | 
 3 | #include "../KICachePolicy.h"
 4 | #include "KArcLruPart.h"
 5 | #include "KArcLfuPart.h"
 6 | #include <memory>
 7 | 
 8 | namespace KamaCache 
 9 | {
10 | 
11 | template<typename Key, typename Value>
12 | class KArcCache : public KICachePolicy<Key, Value> 
13 | {
14 | public:
15 |     explicit KArcCache(size_t capacity = 10, size_t transformThreshold = 2)
16 |         : capacity_(capacity)
17 |         , transformThreshold_(transformThreshold)
18 |         , lruPart_(std::make_unique<ArcLruPart<Key, Value>>(capacity, transformThreshold))
19 |         , lfuPart_(std::make_unique<ArcLfuPart<Key, Value>>(capacity, transformThreshold))
20 |     {}
21 | 
22 |     ~KArcCache() override = default;
23 | 
24 |     void put(Key key, Value value) override 
25 |     {
26 |         checkGhostCaches(key);
27 | 
28 |         // 检查 LFU 部分是否存在该键
29 |         bool inLfu = lfuPart_->contain(key);
30 |         // 更新 LRU 部分缓存
31 |         lruPart_->put(key, value);
32 |         // 如果 LFU 部分存在该键，则更新 LFU 部分
33 |         if (inLfu) 
34 |         {
35 |             lfuPart_->put(key, value);
36 |         }
37 |     }
38 | 
39 |     bool get(Key key, Value& value) override 
40 |     {
41 |         checkGhostCaches(key);
42 | 
43 |         bool shouldTransform = false;
44 |         if (lruPart_->get(key, value, shouldTransform)) 
45 |         {
46 |             if (shouldTransform) 
47 |             {
48 |                 lfuPart_->put(key, value);
49 |             }
50 |             return true;
51 |         }
52 |         return lfuPart_->get(key, value);
53 |     }
54 | 
55 |     Value get(Key key) override 
56 |     {
57 |         Value value{};
58 |         get(key, value);
59 |         return value;
60 |     }
61 | 
62 | private:
63 |     bool checkGhostCaches(Key key) 
64 |     {
65 |         bool inGhost = false;
66 |         if (lruPart_->checkGhost(key)) 
67 |         {
68 |             if (lfuPart_->decreaseCapacity()) 
69 |             {
70 |                 lruPart_->increaseCapacity();
71 |             }
72 |             inGhost = true;
73 |         } 
74 |         else if (lfuPart_->checkGhost(key)) 
75 |         {
76 |             if (lruPart_->decreaseCapacity()) 
77 |             {
78 |                 lfuPart_->increaseCapacity();
79 |             }
80 |             inGhost = true;
81 |         }
82 |         return inGhost;
83 |     }
84 | 
85 | private:
86 |     size_t capacity_;
87 |     size_t transformThreshold_;
88 |     std::unique_ptr<ArcLruPart<Key, Value>> lruPart_;
89 |     std::unique_ptr<ArcLfuPart<Key, Value>> lfuPart_;
90 | };
91 | 
92 | } // namespace KamaCache


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
  1 | # KamaCache
  2 | 
  3 | > **本项目目前只在[知识星球](https://programmercarl.com/other/kstar.html)答疑并维护**。
  4 | 
  5 | 最近很多录友在问：有没有比较小，但又比较完整的项目。
  6 | 
  7 | 最近[知识星球](https://programmercarl.com/other/kstar.html)里里刚刚发布了 C++版本缓存系统，这个小项目。
  8 | 
  9 | 代码量不大，只有1100行。
 10 | 
 11 | 一般的话，每天花 6-8个小时，7天就可以学完。
 12 | 
 13 | 做这个项目的基础要求：
 14 | 
 15 | 熟悉C++语法，学会C++11常用特性即可，了解操作系统相关知识，有网络编程经验更佳。
 16 | 
 17 | 这个项目对于时间紧张的录友比较合适。
 18 | 
 19 | **该项目满足一下特点**：
 20 | 
 21 | * 代码量不大
 22 | * 整体不难
 23 | * 又有项目难点可说的
 24 | * 可以较快学完
 25 | 
 26 | 该缓存系统使用多个页面替换策略实现了**一个线程安全的缓存系统**：
 27 | 
 28 | * LRU：最近最久未使用页面置换算法
 29 | * LFU：最不经常使用页面置换算法
 30 | * ARC：自适应替换缓存算法
 31 | 
 32 | ## 做完本项目，你的收获
 33 | 
 34 | 
 35 | * 掌握缓存的作用、层次结构与设计哲学，理解其在系统架构中的关键价值
 36 | * 亲手实现并优化LRU、LFU、ARC算法，应对不同业务场景
 37 | * 运用互斥锁、原子操作及缓存分片技术，保证多线程数据一致性与高性能
 38 | * 通过分片降低锁竞争、预加载预热缓存，显著提升吞吐量与响应速度
 39 | * 实践应对缓存穿透、击穿、雪崩的行业通用解决方案
 40 | * 从数据结构设计、策略选择到性能评估，获得构建高性能中间件的完整经验
 41 | 
 42 | ## 什么是缓存？
 43 | 
 44 | 缓存是将高频访问的数据暂存到内存中，是加速数据访问的存储，降低延迟，提高吞吐率的利器。
 45 | 
 46 | ## 为什么要实现缓存系统?
 47 | 
 48 | 因缓存的使用相关需求，**通过牺牲一部分服务器内存，减少对磁盘或者数据库资源进行直接读写，可换取更快响应速度**。
 49 | 
 50 | 尤其是处理高并发的场景，负责存储经常访问的数据，通过设计合理的缓存机制提高资源的访问效率。
 51 | 
 52 | 由于服务器的内存是有限的，我们不能把所有数据都存放在内存中，因此需要一种机制来决定当使用内存超过一定标准时，应该删除哪些数据，这就涉及到缓存淘汰策略的选择。
 53 | 
 54 | ## 实际应用场景
 55 | 
 56 | 缓存策略在系统和实际业务开发过程中较为常见，下面我为大家列出一些使用了缓存策略的知名系统和组件：
 57 | 
 58 | **Linux Kernel**： 使用 LRU 在内存管理中页面缓存(Page Cache)，当物理内存不足时，系统会优先淘汰最近未使用的页面。
 59 | 
 60 | **Android内存缓存**：  Android的LRUCache类用于管理有限内存中的应用数据缓存。
 61 | 
 62 | **Redis**：Redis 本身并不直接实现 LRU 缓存策略，但它提供了过期和淘汰机制。
 63 | 
 64 | 在内存不足时，Redis 可以配置不同的淘汰策略，如 volatile-lru（对于设置了过期时间的键，使用 LRU 策略淘汰数据）。
 65 | 
 66 | Redis 提供了 LFU 策略（从 4.0 版本开始）作为其内存驱逐策略之一，可以通过 maxmemory-policy 配置。
 67 | 
 68 | **PostgreSQL** ：在一些PostgreSQL的缓存拓展中实现了基于ARC的缓存机制
 69 | 
 70 | ## 缓存系统项目精讲
 71 | 
 72 | 该项目文档是[知识星球](https://programmercarl.com/other/kstar.html)录友专享的。
 73 | 
 74 | 项目文档依然是将 「简历写法」给大家列出来了，大家学完就可以参考这个来写简历，分别给出普通写法和进阶写法：
 75 | 
 76 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227165531.png' width=500 alt=''></img></div>
 77 | 
 78 | 做完该项目，面试中大概率会有哪些面试问题，以及如何回答，也列出好了，共27道。
 79 | 
 80 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227165754.png' width=500 alt=''></img></div>
 81 | 
 82 | 文档中的项目面试题都掌握的话，这个项目在面试中基本没问题。
 83 | 
 84 | 当然项目文档会对本项目代码做详细的讲解：
 85 | 
 86 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227170954.png' width=500 alt=''></img></div>
 87 | 
 88 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227171014.png' width=500 alt=''></img></div>
 89 | 
 90 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227171042.png' width=500 alt=''></img></div>
 91 | 
 92 | 同时会对三个缓存策略做优劣对对比：
 93 | 
 94 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227171143.png' width=500 alt=''></img></div>
 95 | 
 96 | 同时对缓存命中率做实验效果对比：
 97 | 
 98 | <div align="center"><img src='https://file1.kamacoder.com/i/algo/20241227171342.png' width=500 alt=''></img></div>
 99 | 
100 | ## 答疑
101 | 
102 | 本项目在[知识星球](https://programmercarl.com/other/kstar.html)里为 文字专栏形式，大家不用担心，看不懂，星球里每个项目有专属答疑群，任何问题都可以在群里问，都会得到解答：
103 | 
104 | ![](https://file1.kamacoder.com/i/web/2025-09-26_11-30-13.jpg)
105 | 
106 | 
107 | ## 获取本项目专栏
108 | 
109 | **本文档仅为星球内部专享，大家可以加入[知识星球](https://programmercarl.com/other/kstar.html)里获取，在星球置顶一**
110 | 
111 | 


--------------------------------------------------------------------------------
/KArcCache/KArcLruPart.h:
--------------------------------------------------------------------------------
  1 | #pragma once
  2 | 
  3 | #include "KArcCacheNode.h"
  4 | #include <unordered_map>
  5 | #include <mutex>
  6 | 
  7 | namespace KamaCache 
  8 | {
  9 | 
 10 | template<typename Key, typename Value>
 11 | class ArcLruPart 
 12 | {
 13 | public:
 14 |     using NodeType = ArcNode<Key, Value>;
 15 |     using NodePtr = std::shared_ptr<NodeType>;
 16 |     using NodeMap = std::unordered_map<Key, NodePtr>;
 17 | 
 18 |     explicit ArcLruPart(size_t capacity, size_t transformThreshold)
 19 |         : capacity_(capacity)
 20 |         , ghostCapacity_(capacity)
 21 |         , transformThreshold_(transformThreshold)
 22 |     {
 23 |         initializeLists();
 24 |     }
 25 | 
 26 |     bool put(Key key, Value value) 
 27 |     {
 28 |         if (capacity_ == 0) return false;
 29 |         
 30 |         std::lock_guard<std::mutex> lock(mutex_);
 31 |         auto it = mainCache_.find(key);
 32 |         if (it != mainCache_.end()) 
 33 |         {
 34 |             return updateExistingNode(it->second, value);
 35 |         }
 36 |         return addNewNode(key, value);
 37 |     }
 38 | 
 39 |     bool get(Key key, Value& value, bool& shouldTransform) 
 40 |     {
 41 |         std::lock_guard<std::mutex> lock(mutex_);
 42 |         auto it = mainCache_.find(key);
 43 |         if (it != mainCache_.end()) 
 44 |         {
 45 |             shouldTransform = updateNodeAccess(it->second);
 46 |             value = it->second->getValue();
 47 |             return true;
 48 |         }
 49 |         return false;
 50 |     }
 51 | 
 52 |     bool checkGhost(Key key) 
 53 |     {
 54 |         auto it = ghostCache_.find(key);
 55 |         if (it != ghostCache_.end()) {
 56 |             removeFromGhost(it->second);
 57 |             ghostCache_.erase(it);
 58 |             return true;
 59 |         }
 60 |         return false;
 61 |     }
 62 | 
 63 |     void increaseCapacity() { ++capacity_; }
 64 |     
 65 |     bool decreaseCapacity() 
 66 |     {
 67 |         if (capacity_ <= 0) return false;
 68 |         if (mainCache_.size() == capacity_) {
 69 |             evictLeastRecent();
 70 |         }
 71 |         --capacity_;
 72 |         return true;
 73 |     }
 74 | 
 75 | private:
 76 |     void initializeLists() 
 77 |     {
 78 |         mainHead_ = std::make_shared<NodeType>();
 79 |         mainTail_ = std::make_shared<NodeType>();
 80 |         mainHead_->next_ = mainTail_;
 81 |         mainTail_->prev_ = mainHead_;
 82 | 
 83 |         ghostHead_ = std::make_shared<NodeType>();
 84 |         ghostTail_ = std::make_shared<NodeType>();
 85 |         ghostHead_->next_ = ghostTail_;
 86 |         ghostTail_->prev_ = ghostHead_;
 87 |     }
 88 | 
 89 |     bool updateExistingNode(NodePtr node, const Value& value) 
 90 |     {
 91 |         node->setValue(value);
 92 |         moveToFront(node);
 93 |         return true;
 94 |     }
 95 | 
 96 |     bool addNewNode(const Key& key, const Value& value) 
 97 |     {
 98 |         if (mainCache_.size() >= capacity_) 
 99 |         {   
100 |             evictLeastRecent(); // 驱逐最近最少访问
101 |         }
102 | 
103 |         NodePtr newNode = std::make_shared<NodeType>(key, value);
104 |         mainCache_[key] = newNode;
105 |         addToFront(newNode);
106 |         return true;
107 |     }
108 | 
109 |     bool updateNodeAccess(NodePtr node) 
110 |     {
111 |         moveToFront(node);
112 |         node->incrementAccessCount();
113 |         return node->getAccessCount() >= transformThreshold_;
114 |     }
115 | 
116 |     void moveToFront(NodePtr node) 
117 |     {
118 |         // 先从当前位置移除
119 |         if (!node->prev_.expired() && node->next_) {
120 |             auto prev = node->prev_.lock();
121 |             prev->next_ = node->next_;
122 |             node->next_->prev_ = node->prev_;
123 |             node->next_ = nullptr; // 清空指针，防止悬垂引用
124 |         }
125 |         
126 |         // 添加到头部
127 |         addToFront(node);
128 |     }
129 | 
130 |     void addToFront(NodePtr node) 
131 |     {
132 |         node->next_ = mainHead_->next_;
133 |         node->prev_ = mainHead_;
134 |         mainHead_->next_->prev_ = node;
135 |         mainHead_->next_ = node;
136 |     }
137 | 
138 |     void evictLeastRecent() 
139 |     {
140 |         NodePtr leastRecent = mainTail_->prev_.lock();
141 |         if (!leastRecent || leastRecent == mainHead_) 
142 |             return;
143 | 
144 |         // 从主链表中移除
145 |         removeFromMain(leastRecent);
146 | 
147 |         // 添加到幽灵缓存
148 |         if (ghostCache_.size() >= ghostCapacity_) 
149 |         {
150 |             removeOldestGhost();
151 |         }
152 |         addToGhost(leastRecent);
153 | 
154 |         // 从主缓存映射中移除
155 |         mainCache_.erase(leastRecent->getKey());
156 |     }
157 | 
158 |     void removeFromMain(NodePtr node) 
159 |     {
160 |         if (!node->prev_.expired() && node->next_) {
161 |             auto prev = node->prev_.lock();
162 |             prev->next_ = node->next_;
163 |             node->next_->prev_ = node->prev_;
164 |             node->next_ = nullptr; // 清空指针，防止悬垂引用
165 |         }
166 |     }
167 | 
168 |     void removeFromGhost(NodePtr node) 
169 |     {
170 |         if (!node->prev_.expired() && node->next_) {
171 |             auto prev = node->prev_.lock();
172 |             prev->next_ = node->next_;
173 |             node->next_->prev_ = node->prev_;
174 |             node->next_ = nullptr; // 清空指针，防止悬垂引用
175 |         }
176 |     }
177 | 
178 |     void addToGhost(NodePtr node) 
179 |     {
180 |         // 重置节点的访问计数
181 |         node->accessCount_ = 1;
182 |         
183 |         // 添加到幽灵缓存的头部
184 |         node->next_ = ghostHead_->next_;
185 |         node->prev_ = ghostHead_;
186 |         ghostHead_->next_->prev_ = node;
187 |         ghostHead_->next_ = node;
188 |         
189 |         // 添加到幽灵缓存映射
190 |         ghostCache_[node->getKey()] = node;
191 |     }
192 | 
193 |     void removeOldestGhost() 
194 |     {
195 |         // 使用lock()方法，并添加null检查
196 |         NodePtr oldestGhost = ghostTail_->prev_.lock();
197 |         if (!oldestGhost || oldestGhost == ghostHead_) 
198 |             return;
199 | 
200 |         removeFromGhost(oldestGhost);
201 |         ghostCache_.erase(oldestGhost->getKey());
202 |     }
203 |     
204 | 
205 | private:
206 |     size_t capacity_;
207 |     size_t ghostCapacity_;
208 |     size_t transformThreshold_; // 转换门槛值
209 |     std::mutex mutex_;
210 | 
211 |     NodeMap mainCache_; // key -> ArcNode
212 |     NodeMap ghostCache_;
213 |     
214 |     // 主链表
215 |     NodePtr mainHead_;
216 |     NodePtr mainTail_;
217 |     // 淘汰链表
218 |     NodePtr ghostHead_;
219 |     NodePtr ghostTail_;
220 | };
221 | 
222 | } // namespace KamaCache


--------------------------------------------------------------------------------
/KArcCache/KArcLfuPart.h:
--------------------------------------------------------------------------------
  1 | #pragma once
  2 | 
  3 | #include "KArcCacheNode.h"
  4 | #include <unordered_map>
  5 | #include <map>
  6 | #include <mutex>
  7 | 
  8 | namespace KamaCache 
  9 | {
 10 | 
 11 | template<typename Key, typename Value>
 12 | class ArcLfuPart 
 13 | {
 14 | public:
 15 |     using NodeType = ArcNode<Key, Value>;
 16 |     using NodePtr = std::shared_ptr<NodeType>;
 17 |     using NodeMap = std::unordered_map<Key, NodePtr>;
 18 |     using FreqMap = std::map<size_t, std::list<NodePtr>>;
 19 | 
 20 |     explicit ArcLfuPart(size_t capacity, size_t transformThreshold)
 21 |         : capacity_(capacity)
 22 |         , ghostCapacity_(capacity)
 23 |         , transformThreshold_(transformThreshold)
 24 |         , minFreq_(0)
 25 |     {
 26 |         initializeLists();
 27 |     }
 28 | 
 29 |     bool put(Key key, Value value) 
 30 |     {
 31 |         if (capacity_ == 0) 
 32 |             return false;
 33 | 
 34 |         std::lock_guard<std::mutex> lock(mutex_);
 35 |         auto it = mainCache_.find(key);
 36 |         if (it != mainCache_.end()) 
 37 |         {
 38 |             return updateExistingNode(it->second, value);
 39 |         }
 40 |         return addNewNode(key, value);
 41 |     }
 42 | 
 43 |     bool get(Key key, Value& value) 
 44 |     {
 45 |         std::lock_guard<std::mutex> lock(mutex_);
 46 |         auto it = mainCache_.find(key);
 47 |         if (it != mainCache_.end()) 
 48 |         {
 49 |             updateNodeFrequency(it->second);
 50 |             value = it->second->getValue();
 51 |             return true;
 52 |         }
 53 |         return false;
 54 |     }
 55 | 
 56 |     bool contain(Key key)
 57 |     {
 58 |         return mainCache_.find(key) != mainCache_.end();
 59 |     }
 60 | 
 61 |     bool checkGhost(Key key) 
 62 |     {
 63 |         auto it = ghostCache_.find(key);
 64 |         if (it != ghostCache_.end()) 
 65 |         {
 66 |             removeFromGhost(it->second);
 67 |             ghostCache_.erase(it);
 68 |             return true;
 69 |         }
 70 |         return false;
 71 |     }
 72 | 
 73 |     void increaseCapacity() { ++capacity_; }
 74 |     
 75 |     bool decreaseCapacity() 
 76 |     {
 77 |         if (capacity_ <= 0) return false;
 78 |         if (mainCache_.size() == capacity_) 
 79 |         {
 80 |             evictLeastFrequent();
 81 |         }
 82 |         --capacity_;
 83 |         return true;
 84 |     }
 85 | 
 86 | private:
 87 |     void initializeLists() 
 88 |     {
 89 |         ghostHead_ = std::make_shared<NodeType>();
 90 |         ghostTail_ = std::make_shared<NodeType>();
 91 |         ghostHead_->next_ = ghostTail_;
 92 |         ghostTail_->prev_ = ghostHead_;
 93 |     }
 94 | 
 95 |     bool updateExistingNode(NodePtr node, const Value& value) 
 96 |     {
 97 |         node->setValue(value);
 98 |         updateNodeFrequency(node);
 99 |         return true;
100 |     }
101 | 
102 |     bool addNewNode(const Key& key, const Value& value) 
103 |     {
104 |         if (mainCache_.size() >= capacity_) 
105 |         {
106 |             evictLeastFrequent();
107 |         }
108 | 
109 |         NodePtr newNode = std::make_shared<NodeType>(key, value);
110 |         mainCache_[key] = newNode;
111 |         
112 |         // 将新节点添加到频率为1的列表中
113 |         if (freqMap_.find(1) == freqMap_.end()) 
114 |         {
115 |             freqMap_[1] = std::list<NodePtr>();
116 |         }
117 |         freqMap_[1].push_back(newNode);
118 |         minFreq_ = 1;
119 |         
120 |         return true;
121 |     }
122 | 
123 |     void updateNodeFrequency(NodePtr node) 
124 |     {
125 |         size_t oldFreq = node->getAccessCount();
126 |         node->incrementAccessCount();
127 |         size_t newFreq = node->getAccessCount();
128 | 
129 |         // 从旧频率列表中移除
130 |         auto& oldList = freqMap_[oldFreq];
131 |         oldList.remove(node);
132 |         if (oldList.empty()) 
133 |         {
134 |             freqMap_.erase(oldFreq);
135 |             if (oldFreq == minFreq_) 
136 |             {
137 |                 minFreq_ = newFreq;
138 |             }
139 |         }
140 | 
141 |         // 添加到新频率列表
142 |         if (freqMap_.find(newFreq) == freqMap_.end()) 
143 |         {
144 |             freqMap_[newFreq] = std::list<NodePtr>();
145 |         }
146 |         freqMap_[newFreq].push_back(node);
147 |     }
148 | 
149 |     void evictLeastFrequent() 
150 |     {
151 |         if (freqMap_.empty()) 
152 |             return;
153 | 
154 |         // 获取最小频率的列表
155 |         auto& minFreqList = freqMap_[minFreq_];
156 |         if (minFreqList.empty()) 
157 |             return;
158 | 
159 |         // 移除最少使用的节点
160 |         NodePtr leastNode = minFreqList.front();
161 |         minFreqList.pop_front();
162 | 
163 |         // 如果该频率的列表为空，则删除该频率项
164 |         if (minFreqList.empty()) 
165 |         {
166 |             freqMap_.erase(minFreq_);
167 |             // 更新最小频率
168 |             if (!freqMap_.empty()) 
169 |             {
170 |                 minFreq_ = freqMap_.begin()->first;
171 |             }
172 |         }
173 | 
174 |         // 将节点移到幽灵缓存
175 |         if (ghostCache_.size() >= ghostCapacity_) 
176 |         {
177 |             removeOldestGhost();
178 |         }
179 |         addToGhost(leastNode);
180 |         
181 |         // 从主缓存中移除
182 |         mainCache_.erase(leastNode->getKey());
183 |     }
184 | 
185 |     void removeFromGhost(NodePtr node) 
186 |     {
187 |         if (!node->prev_.expired() && node->next_) {
188 |             auto prev = node->prev_.lock();
189 |             prev->next_ = node->next_;
190 |         node->next_->prev_ = node->prev_;
191 |             node->next_ = nullptr; // 清空指针，防止悬垂引用
192 |         }
193 |     }
194 | 
195 |     void addToGhost(NodePtr node) 
196 |     {
197 |         node->next_ = ghostTail_;
198 |         node->prev_ = ghostTail_->prev_;
199 |         if (!ghostTail_->prev_.expired()) {
200 |             ghostTail_->prev_.lock()->next_ = node;
201 |         }
202 |         ghostTail_->prev_ = node;
203 |         ghostCache_[node->getKey()] = node;
204 |     }
205 | 
206 |     void removeOldestGhost() 
207 |     {
208 |         NodePtr oldestGhost = ghostHead_->next_;
209 |         if (oldestGhost != ghostTail_) 
210 |         {
211 |             removeFromGhost(oldestGhost);
212 |             ghostCache_.erase(oldestGhost->getKey());
213 |         }
214 |     }
215 | 
216 | private:
217 |     size_t capacity_;
218 |     size_t ghostCapacity_;
219 |     size_t transformThreshold_;
220 |     size_t minFreq_;
221 |     std::mutex mutex_;
222 | 
223 |     NodeMap mainCache_;
224 |     NodeMap ghostCache_;
225 |     FreqMap freqMap_;
226 |     
227 |     NodePtr ghostHead_;
228 |     NodePtr ghostTail_;
229 | };
230 | 
231 | } // namespace KamaCache


--------------------------------------------------------------------------------
/KLruCache.h:
--------------------------------------------------------------------------------
  1 | #pragma once 
  2 | 
  3 | #include <cstring>
  4 | #include <list>
  5 | #include <memory>
  6 | #include <mutex>
  7 | #include <unordered_map>
  8 | 
  9 | #include "KICachePolicy.h"
 10 | 
 11 | namespace KamaCache
 12 | {
 13 | 
 14 | // 前向声明
 15 | template<typename Key, typename Value> class KLruCache;
 16 | 
 17 | template<typename Key, typename Value>
 18 | class LruNode 
 19 | {
 20 | private:
 21 |     Key key_;
 22 |     Value value_;
 23 |     size_t accessCount_;  // 访问次数
 24 |     std::weak_ptr<LruNode<Key, Value>> prev_;  // 改为weak_ptr打破循环引用
 25 |     std::shared_ptr<LruNode<Key, Value>> next_;
 26 | 
 27 | public:
 28 |     LruNode(Key key, Value value)
 29 |         : key_(key)
 30 |         , value_(value)
 31 |         , accessCount_(1) 
 32 |     {}
 33 | 
 34 |     // 提供必要的访问器
 35 |     Key getKey() const { return key_; }
 36 |     Value getValue() const { return value_; }
 37 |     void setValue(const Value& value) { value_ = value; }
 38 |     size_t getAccessCount() const { return accessCount_; }
 39 |     void incrementAccessCount() { ++accessCount_; }
 40 | 
 41 |     friend class KLruCache<Key, Value>;
 42 | };
 43 | 
 44 | 
 45 | template<typename Key, typename Value>
 46 | class KLruCache : public KICachePolicy<Key, Value>
 47 | {
 48 | public:
 49 |     using LruNodeType = LruNode<Key, Value>;
 50 |     using NodePtr = std::shared_ptr<LruNodeType>;
 51 |     using NodeMap = std::unordered_map<Key, NodePtr>;
 52 | 
 53 |     KLruCache(int capacity)
 54 |         : capacity_(capacity)
 55 |     {
 56 |         initializeList();
 57 |     }
 58 | 
 59 |     ~KLruCache() override = default;
 60 | 
 61 |     // 添加缓存
 62 |     void put(Key key, Value value) override
 63 |     {
 64 |         if (capacity_ <= 0)
 65 |             return;
 66 |     
 67 |         std::lock_guard<std::mutex> lock(mutex_);
 68 |         auto it = nodeMap_.find(key);
 69 |         if (it != nodeMap_.end())
 70 |         {
 71 |             // 如果在当前容器中,则更新value,并调用get方法，代表该数据刚被访问
 72 |             updateExistingNode(it->second, value);
 73 |             return ;
 74 |         }
 75 | 
 76 |         addNewNode(key, value);
 77 |     }
 78 | 
 79 |     bool get(Key key, Value& value) override
 80 |     {
 81 |         std::lock_guard<std::mutex> lock(mutex_);
 82 |         auto it = nodeMap_.find(key);
 83 |         if (it != nodeMap_.end())
 84 |         {
 85 |             moveToMostRecent(it->second);
 86 |             value = it->second->getValue();
 87 |             return true;
 88 |         }
 89 |         return false;
 90 |     }
 91 | 
 92 |     Value get(Key key) override
 93 |     {
 94 |         Value value{};
 95 |         // memset(&value, 0, sizeof(value));   // memset 是按字节设置内存的，对于复杂类型（如 string）使用 memset 可能会破坏对象的内部结构
 96 |         get(key, value);
 97 |         return value;
 98 |     }
 99 | 
100 |     // 删除指定元素
101 |     void remove(Key key) 
102 |     {   
103 |         std::lock_guard<std::mutex> lock(mutex_);
104 |         auto it = nodeMap_.find(key);
105 |         if (it != nodeMap_.end())
106 |         {
107 |             removeNode(it->second);
108 |             nodeMap_.erase(it);
109 |         }
110 |     }
111 | 
112 | private:
113 |     void initializeList()
114 |     {
115 |         // 创建首尾虚拟节点
116 |         dummyHead_ = std::make_shared<LruNodeType>(Key(), Value());
117 |         dummyTail_ = std::make_shared<LruNodeType>(Key(), Value());
118 |         dummyHead_->next_ = dummyTail_;
119 |         dummyTail_->prev_ = dummyHead_;
120 |     }
121 | 
122 |     void updateExistingNode(NodePtr node, const Value& value) 
123 |     {
124 |         node->setValue(value);
125 |         moveToMostRecent(node);
126 |     }
127 | 
128 |     void addNewNode(const Key& key, const Value& value) 
129 |     {
130 |        if (nodeMap_.size() >= capacity_) 
131 |        {
132 |            evictLeastRecent();
133 |        }
134 | 
135 |        NodePtr newNode = std::make_shared<LruNodeType>(key, value);
136 |        insertNode(newNode);
137 |        nodeMap_[key] = newNode;
138 |     }
139 | 
140 |     // 将该节点移动到最新的位置
141 |     void moveToMostRecent(NodePtr node) 
142 |     {
143 |         removeNode(node);
144 |         insertNode(node);
145 |     }
146 | 
147 |     void removeNode(NodePtr node) 
148 |     {
149 |         if(!node->prev_.expired() && node->next_) 
150 |         {
151 |             auto prev = node->prev_.lock(); // 使用lock()获取shared_ptr
152 |             prev->next_ = node->next_;
153 |             node->next_->prev_ = prev;
154 |             node->next_ = nullptr; // 清空next_指针，彻底断开节点与链表的连接
155 |         }
156 |     }
157 | 
158 |     // 从尾部插入结点
159 |     void insertNode(NodePtr node) 
160 |     {
161 |         node->next_ = dummyTail_;
162 |         node->prev_ = dummyTail_->prev_;
163 |         dummyTail_->prev_.lock()->next_ = node; // 使用lock()获取shared_ptr
164 |         dummyTail_->prev_ = node;
165 |     }
166 | 
167 |     // 驱逐最近最少访问
168 |     void evictLeastRecent() 
169 |     {
170 |         NodePtr leastRecent = dummyHead_->next_;
171 |         removeNode(leastRecent);
172 |         nodeMap_.erase(leastRecent->getKey());
173 |     }
174 | 
175 | private:
176 |     int           capacity_; // 缓存容量
177 |     NodeMap       nodeMap_; // key -> Node 
178 |     std::mutex    mutex_;
179 |     NodePtr       dummyHead_; // 虚拟头结点
180 |     NodePtr       dummyTail_;
181 | };
182 | 
183 | // LRU优化：Lru-k版本。 通过继承的方式进行再优化
184 | template<typename Key, typename Value>
185 | class KLruKCache : public KLruCache<Key, Value>
186 | {
187 | public:
188 |     KLruKCache(int capacity, int historyCapacity, int k)
189 |         : KLruCache<Key, Value>(capacity) // 调用基类构造
190 |         , historyList_(std::make_unique<KLruCache<Key, size_t>>(historyCapacity))
191 |         , k_(k)
192 |     {}
193 | 
194 |     Value get(Key key) 
195 |     {
196 |         // 首先尝试从主缓存获取数据
197 |         Value value{};
198 |         bool inMainCache = KLruCache<Key, Value>::get(key, value);
199 | 
200 |         // 获取并更新访问历史计数
201 |         size_t historyCount = historyList_->get(key);
202 |         historyCount++;
203 |         historyList_->put(key, historyCount);
204 | 
205 |         // 如果数据在主缓存中，直接返回
206 |         if (inMainCache) 
207 |         {
208 |             return value;
209 |         }
210 | 
211 |         // 如果数据不在主缓存，但访问次数达到了k次
212 |         if (historyCount >= k_) 
213 |         {
214 |             // 检查是否有历史值记录
215 |             auto it = historyValueMap_.find(key);
216 |             if (it != historyValueMap_.end()) 
217 |             {
218 |                 // 有历史值，将其添加到主缓存
219 |                 Value storedValue = it->second;
220 |                 
221 |                 // 从历史记录移除
222 |                 historyList_->remove(key);
223 |                 historyValueMap_.erase(it);
224 |                 
225 |                 // 添加到主缓存
226 |                 KLruCache<Key, Value>::put(key, storedValue);
227 |                 
228 |                 return storedValue;
229 |             }
230 |             // 没有历史值记录，无法添加到缓存，返回默认值
231 |         }
232 | 
233 |         // 数据不在主缓存且不满足添加条件，返回默认值
234 |         return value;
235 |     }
236 | 
237 |     void put(Key key, Value value) 
238 |     {
239 |         // 检查是否已在主缓存
240 |         Value existingValue{};
241 |         bool inMainCache = KLruCache<Key, Value>::get(key, existingValue);
242 |         
243 |         if (inMainCache) 
244 |         {
245 |             // 已在主缓存，直接更新
246 |             KLruCache<Key, Value>::put(key, value);
247 |             return;
248 |         }
249 |         
250 |         // 获取并更新访问历史
251 |         size_t historyCount = historyList_->get(key);
252 |         historyCount++;
253 |         historyList_->put(key, historyCount);
254 |         
255 |         // 保存值到历史记录映射，供后续get操作使用
256 |         historyValueMap_[key] = value;
257 |         
258 |         // 检查是否达到k次访问阈值
259 |         if (historyCount >= k_) 
260 |         {
261 |             // 达到阈值，添加到主缓存
262 |             historyList_->remove(key);
263 |             historyValueMap_.erase(key);
264 |             KLruCache<Key, Value>::put(key, value);
265 |         }
266 |     }
267 | 
268 | private:
269 |     int                                     k_; // 进入缓存队列的评判标准
270 |     std::unique_ptr<KLruCache<Key, size_t>> historyList_; // 访问数据历史记录(value为访问次数)
271 |     std::unordered_map<Key, Value>          historyValueMap_; // 存储未达到k次访问的数据值
272 | };
273 | 
274 | // lru优化：对lru进行分片，提高高并发使用的性能
275 | template<typename Key, typename Value>
276 | class KHashLruCaches
277 | {
278 | public:
279 |     KHashLruCaches(size_t capacity, int sliceNum)
280 |         : capacity_(capacity)
281 |         , sliceNum_(sliceNum > 0 ? sliceNum : std::thread::hardware_concurrency())
282 |     {
283 |         size_t sliceSize = std::ceil(capacity / static_cast<double>(sliceNum_)); // 获取每个分片的大小
284 |         for (int i = 0; i < sliceNum_; ++i)
285 |         {
286 |             lruSliceCaches_.emplace_back(new KLruCache<Key, Value>(sliceSize)); 
287 |         }
288 |     }
289 | 
290 |     void put(Key key, Value value)
291 |     {
292 |         // 获取key的hash值，并计算出对应的分片索引
293 |         size_t sliceIndex = Hash(key) % sliceNum_;
294 |         lruSliceCaches_[sliceIndex]->put(key, value);
295 |     }
296 | 
297 |     bool get(Key key, Value& value)
298 |     {
299 |         // 获取key的hash值，并计算出对应的分片索引
300 |         size_t sliceIndex = Hash(key) % sliceNum_;
301 |         return lruSliceCaches_[sliceIndex]->get(key, value);
302 |     }
303 | 
304 |     Value get(Key key)
305 |     {
306 |         Value value;
307 |         memset(&value, 0, sizeof(value));
308 |         get(key, value);
309 |         return value;
310 |     }
311 | 
312 | private:
313 |     // 将key转换为对应hash值
314 |     size_t Hash(Key key)
315 |     {
316 |         std::hash<Key> hashFunc;
317 |         return hashFunc(key);
318 |     }
319 | 
320 | private:
321 |     size_t                                              capacity_;  // 总容量
322 |     int                                                 sliceNum_;  // 切片数量
323 |     std::vector<std::unique_ptr<KLruCache<Key, Value>>> lruSliceCaches_; // 切片LRU缓存
324 | };
325 | 
326 | } // namespace KamaCache


--------------------------------------------------------------------------------
/KLfuCache.h:
--------------------------------------------------------------------------------
  1 | #pragma once
  2 | 
  3 | #include <cmath>
  4 | #include <memory>
  5 | #include <mutex>
  6 | #include <thread>
  7 | #include <unordered_map>
  8 | #include <vector>
  9 | 
 10 | #include "KICachePolicy.h"
 11 | 
 12 | namespace KamaCache
 13 | {
 14 | 
 15 | template<typename Key, typename Value> class KLfuCache;
 16 | 
 17 | template<typename Key, typename Value>
 18 | class FreqList
 19 | {
 20 | private:
 21 |     struct Node
 22 |     {
 23 |         int freq; // 访问频次
 24 |         Key key;
 25 |         Value value;
 26 |         std::weak_ptr<Node> pre; // 上一结点改为weak_ptr打破循环引用
 27 |         std::shared_ptr<Node> next;
 28 | 
 29 |         Node() 
 30 |         : freq(1), next(nullptr) {}
 31 |         Node(Key key, Value value) 
 32 |         : freq(1), key(key), value(value), next(nullptr) {}
 33 |     };
 34 | 
 35 |     using NodePtr = std::shared_ptr<Node>;
 36 |     int freq_; // 访问频率
 37 |     NodePtr head_; // 假头结点
 38 |     NodePtr tail_; // 假尾结点
 39 | 
 40 | public:
 41 |     explicit FreqList(int n) 
 42 |      : freq_(n) 
 43 |     {
 44 |       head_ = std::make_shared<Node>();
 45 |       tail_ = std::make_shared<Node>();
 46 |       head_->next = tail_;
 47 |       tail_->pre = head_;
 48 |     }
 49 | 
 50 |     bool isEmpty() const
 51 |     {
 52 |       return head_->next == tail_;
 53 |     }
 54 | 
 55 |     // 提那家结点管理方法
 56 |     void addNode(NodePtr node) 
 57 |     {
 58 |         if (!node || !head_ || !tail_) 
 59 |             return;
 60 | 
 61 |         node->pre = tail_->pre;
 62 |         node->next = tail_;
 63 |         tail_->pre.lock()->next = node; // 使用lock()获取shared_ptr
 64 |         tail_->pre = node;
 65 |     }
 66 | 
 67 |     void removeNode(NodePtr node)
 68 |     {
 69 |         if (!node || !head_ || !tail_)
 70 |             return;
 71 |         if (node->pre.expired() || !node->next) 
 72 |             return;
 73 | 
 74 |         auto pre = node->pre.lock(); // 使用lock()获取shared_ptr
 75 |         pre->next = node->next;
 76 |         node->next->pre = pre;
 77 |         node->next = nullptr; // 确保显式置空next指针，彻底断开节点与链表的连接
 78 |     }
 79 | 
 80 |     NodePtr getFirstNode() const { return head_->next; }
 81 |     
 82 |     friend class KLfuCache<Key, Value>;
 83 | };
 84 | 
 85 | template <typename Key, typename Value>
 86 | class KLfuCache : public KICachePolicy<Key, Value>
 87 | {
 88 | public:
 89 |     using Node = typename FreqList<Key, Value>::Node;
 90 |     using NodePtr = std::shared_ptr<Node>;
 91 |     using NodeMap = std::unordered_map<Key, NodePtr>;
 92 | 
 93 |     KLfuCache(int capacity, int maxAverageNum = 1000000)
 94 |     : capacity_(capacity), minFreq_(INT8_MAX), maxAverageNum_(maxAverageNum),
 95 |       curAverageNum_(0), curTotalNum_(0) 
 96 |     {}
 97 | 
 98 |     ~KLfuCache() override = default;
 99 | 
100 |     void put(Key key, Value value) override
101 |     {
102 |         if (capacity_ == 0)
103 |             return;
104 | 
105 |         std::lock_guard<std::mutex> lock(mutex_);
106 |         auto it = nodeMap_.find(key);
107 |         if (it != nodeMap_.end())
108 |         {
109 |             // 重置其value值
110 |             it->second->value = value;
111 |             // 找到了直接调整就好了，不用再去get中再找一遍，但其实影响不大
112 |             getInternal(it->second, value);
113 |             return;
114 |         }
115 | 
116 |         putInternal(key, value);
117 |     }
118 | 
119 |     // value值为传出参数
120 |     bool get(Key key, Value& value) override
121 |     {
122 |       std::lock_guard<std::mutex> lock(mutex_);
123 |       auto it = nodeMap_.find(key);
124 |       if (it != nodeMap_.end())
125 |       {
126 |           getInternal(it->second, value);
127 |           return true;
128 |       }
129 | 
130 |       return false;
131 |     }
132 | 
133 |     Value get(Key key) override
134 |     {
135 |       Value value;
136 |       get(key, value);
137 |       return value;
138 |     }
139 | 
140 |       // 清空缓存,回收资源
141 |     void purge()
142 |     {
143 |       nodeMap_.clear();
144 |       freqToFreqList_.clear();
145 |     }
146 | 
147 | private:
148 |     void putInternal(Key key, Value value); // 添加缓存
149 |     void getInternal(NodePtr node, Value& value); // 获取缓存
150 | 
151 |     void kickOut(); // 移除缓存中的过期数据
152 | 
153 |     void removeFromFreqList(NodePtr node); // 从频率列表中移除节点
154 |     void addToFreqList(NodePtr node); // 添加到频率列表
155 | 
156 |     void addFreqNum(); // 增加平均访问等频率
157 |     void decreaseFreqNum(int num); // 减少平均访问等频率
158 |     void handleOverMaxAverageNum(); // 处理当前平均访问频率超过上限的情况
159 |     void updateMinFreq();
160 | 
161 | private:
162 |     int                                            capacity_; // 缓存容量
163 |     int                                            minFreq_; // 最小访问频次(用于找到最小访问频次结点)
164 |     int                                            maxAverageNum_; // 最大平均访问频次
165 |     int                                            curAverageNum_; // 当前平均访问频次
166 |     int                                            curTotalNum_; // 当前访问所有缓存次数总数 
167 |     std::mutex                                     mutex_; // 互斥锁
168 |     NodeMap                                        nodeMap_; // key 到 缓存节点的映射
169 |     std::unordered_map<int, FreqList<Key, Value>*> freqToFreqList_;// 访问频次到该频次链表的映射
170 | };
171 | 
172 | template<typename Key, typename Value>
173 | void KLfuCache<Key, Value>::getInternal(NodePtr node, Value& value)
174 | {
175 |     // 找到之后需要将其从低访问频次的链表中删除，并且添加到+1的访问频次链表中，
176 |     // 访问频次+1, 然后把value值返回
177 |     value = node->value;
178 |     // 从原有访问频次的链表中删除节点
179 |     removeFromFreqList(node); 
180 |     node->freq++;
181 |     addToFreqList(node);
182 |     // 如果当前node的访问频次如果等于minFreq+1，并且其前驱链表为空，则说明
183 |     // freqToFreqList_[node->freq - 1]链表因node的迁移已经空了，需要更新最小访问频次
184 |     if (node->freq - 1 == minFreq_ && freqToFreqList_[node->freq - 1]->isEmpty())
185 |         minFreq_++;
186 | 
187 |     // 总访问频次和当前平均访问频次都随之增加
188 |     addFreqNum();
189 | }
190 | 
191 | template<typename Key, typename Value>
192 | void KLfuCache<Key, Value>::putInternal(Key key, Value value)
193 | {   
194 |     // 如果不在缓存中，则需要判断缓存是否已满
195 |     if (nodeMap_.size() == capacity_)
196 |     {
197 |         // 缓存已满，删除最不常访问的结点，更新当前平均访问频次和总访问频次
198 |         kickOut();
199 |     }
200 |     
201 |     // 创建新结点，将新结点添加进入，更新最小访问频次
202 |     NodePtr node = std::make_shared<Node>(key, value);
203 |     nodeMap_[key] = node;
204 |     addToFreqList(node);
205 |     addFreqNum();
206 |     minFreq_ = std::min(minFreq_, 1);
207 | }
208 | 
209 | template<typename Key, typename Value>
210 | void KLfuCache<Key, Value>::kickOut()
211 | {
212 |     NodePtr node = freqToFreqList_[minFreq_]->getFirstNode();
213 |     removeFromFreqList(node);
214 |     nodeMap_.erase(node->key);
215 |     decreaseFreqNum(node->freq);
216 | }
217 | 
218 | template<typename Key, typename Value>
219 | void KLfuCache<Key, Value>::removeFromFreqList(NodePtr node)
220 | {
221 |     // 检查结点是否为空
222 |     if (!node) 
223 |         return;
224 |     
225 |     auto freq = node->freq;
226 |     freqToFreqList_[freq]->removeNode(node);
227 | }
228 | 
229 | template<typename Key, typename Value>
230 | void KLfuCache<Key, Value>::addToFreqList(NodePtr node)
231 | {
232 |     // 检查结点是否为空
233 |     if (!node) 
234 |         return;
235 | 
236 |     // 添加进入相应的频次链表前需要判断该频次链表是否存在
237 |     auto freq = node->freq;
238 |     if (freqToFreqList_.find(node->freq) == freqToFreqList_.end())
239 |     {
240 |         // 不存在则创建
241 |         freqToFreqList_[node->freq] = new FreqList<Key, Value>(node->freq);
242 |     }
243 | 
244 |     freqToFreqList_[freq]->addNode(node);
245 | }
246 | 
247 | template<typename Key, typename Value>
248 | void KLfuCache<Key, Value>::addFreqNum()
249 | {
250 |     curTotalNum_++;
251 |     if (nodeMap_.empty())
252 |         curAverageNum_ = 0;
253 |     else
254 |         curAverageNum_ = curTotalNum_ / nodeMap_.size();
255 | 
256 |     if (curAverageNum_ > maxAverageNum_)
257 |     {
258 |        handleOverMaxAverageNum();
259 |     }
260 | }
261 | 
262 | template<typename Key, typename Value>
263 | void KLfuCache<Key, Value>::decreaseFreqNum(int num)
264 | {
265 |     // 减少平均访问频次和总访问频次
266 |     curTotalNum_ -= num;
267 |     if (nodeMap_.empty())
268 |         curAverageNum_ = 0;
269 |     else
270 |         curAverageNum_ = curTotalNum_ / nodeMap_.size();
271 | }
272 | 
273 | template<typename Key, typename Value>
274 | void KLfuCache<Key, Value>::handleOverMaxAverageNum()
275 | {
276 |     if (nodeMap_.empty())
277 |         return;
278 | 
279 |     // 当前平均访问频次已经超过了最大平均访问频次，所有结点的访问频次- (maxAverageNum_ / 2)
280 |     for (auto it = nodeMap_.begin(); it != nodeMap_.end(); ++it)
281 |     {
282 |         // 检查结点是否为空
283 |         if (!it->second)
284 |             continue;
285 | 
286 |         NodePtr node = it->second;
287 | 
288 |         // 先从当前频率列表中移除
289 |         removeFromFreqList(node);
290 | 
291 |         // 减少频率
292 |         node->freq -= maxAverageNum_ / 2;
293 |         if (node->freq < 1) node->freq = 1;
294 | 
295 |         // 添加到新的频率列表
296 |         addToFreqList(node);
297 |     }
298 | 
299 |     // 更新最小频率
300 |     updateMinFreq();
301 | }
302 | 
303 | template<typename Key, typename Value>
304 | void KLfuCache<Key, Value>::updateMinFreq() 
305 | {
306 |     minFreq_ = INT8_MAX;
307 |     for (const auto& pair : freqToFreqList_) 
308 |     {
309 |         if (pair.second && !pair.second->isEmpty()) 
310 |         {
311 |             minFreq_ = std::min(minFreq_, pair.first);
312 |         }
313 |     }
314 |     if (minFreq_ == INT8_MAX) 
315 |         minFreq_ = 1;
316 | }
317 | 
318 | // 并没有牺牲空间换时间，他是把原有缓存大小进行了分片。
319 | template<typename Key, typename Value>
320 | class KHashLfuCache
321 | {
322 | public:
323 |     KHashLfuCache(size_t capacity, int sliceNum, int maxAverageNum = 10)
324 |         : sliceNum_(sliceNum > 0 ? sliceNum : std::thread::hardware_concurrency())
325 |         , capacity_(capacity)
326 |     {
327 |         size_t sliceSize = std::ceil(capacity_ / static_cast<double>(sliceNum_)); // 每个lfu分片的容量
328 |         for (int i = 0; i < sliceNum_; ++i)
329 |         {
330 |             lfuSliceCaches_.emplace_back(new KLfuCache<Key, Value>(sliceSize, maxAverageNum));
331 |         }
332 |     }
333 | 
334 |     void put(Key key, Value value)
335 |     {
336 |         // 根据key找出对应的lfu分片
337 |         size_t sliceIndex = Hash(key) % sliceNum_;
338 |         lfuSliceCaches_[sliceIndex]->put(key, value);
339 |     }
340 | 
341 |     bool get(Key key, Value& value)
342 |     {
343 |         // 根据key找出对应的lfu分片
344 |         size_t sliceIndex = Hash(key) % sliceNum_;
345 |         return lfuSliceCaches_[sliceIndex]->get(key, value);
346 |     }
347 | 
348 |     Value get(Key key)
349 |     {
350 |         Value value;
351 |         get(key, value);
352 |         return value;
353 |     }
354 | 
355 |     // 清除缓存
356 |     void purge()
357 |     {
358 |         for (auto& lfuSliceCache : lfuSliceCaches_)
359 |         {
360 |             lfuSliceCache->purge();
361 |         }
362 |     }
363 | 
364 | private:
365 |     // 将key计算成对应哈希值
366 |     size_t Hash(Key key)
367 |     {
368 |         std::hash<Key> hashFunc;
369 |         return hashFunc(key);
370 |     }
371 | 
372 | private:
373 |     size_t capacity_; // 缓存总容量
374 |     int sliceNum_; // 缓存分片数量
375 |     std::vector<std::unique_ptr<KLfuCache<Key, Value>>> lfuSliceCaches_; // 缓存lfu分片容器
376 | };
377 | 
378 | } // namespace KamaCache
379 | 
380 | 


--------------------------------------------------------------------------------
/testAllCachePolicy.cpp:
--------------------------------------------------------------------------------
  1 | #include <iostream>
  2 | #include <string>
  3 | #include <chrono>
  4 | #include <vector>
  5 | #include <iomanip>
  6 | #include <random>
  7 | #include <algorithm>
  8 | 
  9 | #include "KICachePolicy.h"
 10 | #include "KLfuCache.h"
 11 | #include "KLruCache.h"
 12 | #include "KArcCache/KArcCache.h"
 13 | 
 14 | class Timer {
 15 | public:
 16 |     Timer() : start_(std::chrono::high_resolution_clock::now()) {}
 17 |     
 18 |     double elapsed() {
 19 |         auto now = std::chrono::high_resolution_clock::now();
 20 |         return std::chrono::duration_cast<std::chrono::milliseconds>(now - start_).count();
 21 |     }
 22 | 
 23 | private:
 24 |     std::chrono::time_point<std::chrono::high_resolution_clock> start_;
 25 | };
 26 | 
 27 | // 辅助函数：打印结果
 28 | void printResults(const std::string& testName, int capacity, 
 29 |                  const std::vector<int>& get_operations, 
 30 |                  const std::vector<int>& hits) {
 31 |     std::cout << "=== " << testName << " 结果汇总 ===" << std::endl;
 32 |     std::cout << "缓存大小: " << capacity << std::endl;
 33 |     
 34 |     // 假设对应的算法名称已在测试函数中定义
 35 |     std::vector<std::string> names;
 36 |     if (hits.size() == 3) {
 37 |         names = {"LRU", "LFU", "ARC"};
 38 |     } else if (hits.size() == 4) {
 39 |         names = {"LRU", "LFU", "ARC", "LRU-K"};
 40 |     } else if (hits.size() == 5) {
 41 |         names = {"LRU", "LFU", "ARC", "LRU-K", "LFU-Aging"};
 42 |     }
 43 |     
 44 |     for (size_t i = 0; i < hits.size(); ++i) {
 45 |         double hitRate = 100.0 * hits[i] / get_operations[i];
 46 |         std::cout << (i < names.size() ? names[i] : "Algorithm " + std::to_string(i+1)) 
 47 |                   << " - 命中率: " << std::fixed << std::setprecision(2) 
 48 |                   << hitRate << "% ";
 49 |         // 添加具体命中次数和总操作次数
 50 |         std::cout << "(" << hits[i] << "/" << get_operations[i] << ")" << std::endl;
 51 |     }
 52 |     
 53 |     std::cout << std::endl;  // 添加空行，使输出更清晰
 54 | }
 55 | 
 56 | void testHotDataAccess() {
 57 |     std::cout << "\n=== 测试场景1：热点数据访问测试 ===" << std::endl;
 58 |     
 59 |     const int CAPACITY = 20;         // 缓存容量
 60 |     const int OPERATIONS = 500000;   // 总操作次数
 61 |     const int HOT_KEYS = 20;         // 热点数据数量
 62 |     const int COLD_KEYS = 5000;      // 冷数据数量
 63 |     
 64 |     KamaCache::KLruCache<int, std::string> lru(CAPACITY);
 65 |     KamaCache::KLfuCache<int, std::string> lfu(CAPACITY);
 66 |     KamaCache::KArcCache<int, std::string> arc(CAPACITY);
 67 |     // 为LRU-K设置合适的参数：
 68 |     // - 主缓存容量与其他算法相同
 69 |     // - 历史记录容量设为可能访问的所有键数量
 70 |     // - k=2表示数据被访问2次后才会进入缓存，适合区分热点和冷数据
 71 |     KamaCache::KLruKCache<int, std::string> lruk(CAPACITY, HOT_KEYS + COLD_KEYS, 2);
 72 |     KamaCache::KLfuCache<int, std::string> lfuAging(CAPACITY, 20000);
 73 | 
 74 |     std::random_device rd;
 75 |     std::mt19937 gen(rd());
 76 |     
 77 |     // 基类指针指向派生类对象，添加LFU-Aging
 78 |     std::array<KamaCache::KICachePolicy<int, std::string>*, 5> caches = {&lru, &lfu, &arc, &lruk, &lfuAging};
 79 |     std::vector<int> hits(5, 0);
 80 |     std::vector<int> get_operations(5, 0);
 81 |     std::vector<std::string> names = {"LRU", "LFU", "ARC", "LRU-K", "LFU-Aging"};
 82 | 
 83 |     // 为所有的缓存对象进行相同的操作序列测试
 84 |     for (int i = 0; i < caches.size(); ++i) {
 85 |         // 先预热缓存，插入一些数据
 86 |         for (int key = 0; key < HOT_KEYS; ++key) {
 87 |             std::string value = "value" + std::to_string(key);
 88 |             caches[i]->put(key, value);
 89 |         }
 90 |         
 91 |         // 交替进行put和get操作，模拟真实场景
 92 |         for (int op = 0; op < OPERATIONS; ++op) {
 93 |             // 大多数缓存系统中读操作比写操作频繁
 94 |             // 所以设置30%概率进行写操作
 95 |             bool isPut = (gen() % 100 < 30); 
 96 |             int key;
 97 |             
 98 |             // 70%概率访问热点数据，30%概率访问冷数据
 99 |             if (gen() % 100 < 70) {
100 |                 key = gen() % HOT_KEYS; // 热点数据
101 |             } else {
102 |                 key = HOT_KEYS + (gen() % COLD_KEYS); // 冷数据
103 |             }
104 |             
105 |             if (isPut) {
106 |                 // 执行put操作
107 |                 std::string value = "value" + std::to_string(key) + "_v" + std::to_string(op % 100);
108 |                 caches[i]->put(key, value);
109 |             } else {
110 |                 // 执行get操作并记录命中情况
111 |                 std::string result;
112 |                 get_operations[i]++;
113 |                 if (caches[i]->get(key, result)) {
114 |                     hits[i]++;
115 |                 }
116 |             }
117 |         }
118 |     }
119 | 
120 |     // 打印测试结果
121 |     printResults("热点数据访问测试", CAPACITY, get_operations, hits);
122 | }
123 | 
124 | void testLoopPattern() {
125 |     std::cout << "\n=== 测试场景2：循环扫描测试 ===" << std::endl;
126 |     
127 |     const int CAPACITY = 50;          // 缓存容量
128 |     const int LOOP_SIZE = 500;        // 循环范围大小
129 |     const int OPERATIONS = 200000;    // 总操作次数
130 |     
131 |     KamaCache::KLruCache<int, std::string> lru(CAPACITY);
132 |     KamaCache::KLfuCache<int, std::string> lfu(CAPACITY);
133 |     KamaCache::KArcCache<int, std::string> arc(CAPACITY);
134 |     // 为LRU-K设置合适的参数：
135 |     // - 历史记录容量设为总循环大小的两倍，覆盖范围内和范围外的数据
136 |     // - k=2，对于循环访问，这是一个合理的阈值
137 |     KamaCache::KLruKCache<int, std::string> lruk(CAPACITY, LOOP_SIZE * 2, 2);
138 |     KamaCache::KLfuCache<int, std::string> lfuAging(CAPACITY, 3000);
139 | 
140 |     std::array<KamaCache::KICachePolicy<int, std::string>*, 5> caches = {&lru, &lfu, &arc, &lruk, &lfuAging};
141 |     std::vector<int> hits(5, 0);
142 |     std::vector<int> get_operations(5, 0);
143 |     std::vector<std::string> names = {"LRU", "LFU", "ARC", "LRU-K", "LFU-Aging"};
144 | 
145 |     std::random_device rd;
146 |     std::mt19937 gen(rd());
147 | 
148 |     // 为每种缓存算法运行相同的测试
149 |     for (int i = 0; i < caches.size(); ++i) {
150 |         // 先预热一部分数据（只加载20%的数据）
151 |         for (int key = 0; key < LOOP_SIZE / 5; ++key) {
152 |             std::string value = "loop" + std::to_string(key);
153 |             caches[i]->put(key, value);
154 |         }
155 |         
156 |         // 设置循环扫描的当前位置
157 |         int current_pos = 0;
158 |         
159 |         // 交替进行读写操作，模拟真实场景
160 |         for (int op = 0; op < OPERATIONS; ++op) {
161 |             // 20%概率是写操作，80%概率是读操作
162 |             bool isPut = (gen() % 100 < 20);
163 |             int key;
164 |             
165 |             // 按照不同模式选择键
166 |             if (op % 100 < 60) {  // 60%顺序扫描
167 |                 key = current_pos;
168 |                 current_pos = (current_pos + 1) % LOOP_SIZE;
169 |             } else if (op % 100 < 90) {  // 30%随机跳跃
170 |                 key = gen() % LOOP_SIZE;
171 |             } else {  // 10%访问范围外数据
172 |                 key = LOOP_SIZE + (gen() % LOOP_SIZE);
173 |             }
174 |             
175 |             if (isPut) {
176 |                 // 执行put操作，更新数据
177 |                 std::string value = "loop" + std::to_string(key) + "_v" + std::to_string(op % 100);
178 |                 caches[i]->put(key, value);
179 |             } else {
180 |                 // 执行get操作并记录命中情况
181 |                 std::string result;
182 |                 get_operations[i]++;
183 |                 if (caches[i]->get(key, result)) {
184 |                     hits[i]++;
185 |                 }
186 |             }
187 |         }
188 |     }
189 | 
190 |     printResults("循环扫描测试", CAPACITY, get_operations, hits);
191 | }
192 | 
193 | void testWorkloadShift() {
194 |     std::cout << "\n=== 测试场景3：工作负载剧烈变化测试 ===" << std::endl;
195 |     
196 |     const int CAPACITY = 30;            // 缓存容量
197 |     const int OPERATIONS = 80000;       // 总操作次数
198 |     const int PHASE_LENGTH = OPERATIONS / 5;  // 每个阶段的长度
199 |     
200 |     KamaCache::KLruCache<int, std::string> lru(CAPACITY);
201 |     KamaCache::KLfuCache<int, std::string> lfu(CAPACITY);
202 |     KamaCache::KArcCache<int, std::string> arc(CAPACITY);
203 |     KamaCache::KLruKCache<int, std::string> lruk(CAPACITY, 500, 2);
204 |     KamaCache::KLfuCache<int, std::string> lfuAging(CAPACITY, 10000);
205 | 
206 |     std::random_device rd;
207 |     std::mt19937 gen(rd());
208 |     std::array<KamaCache::KICachePolicy<int, std::string>*, 5> caches = {&lru, &lfu, &arc, &lruk, &lfuAging};
209 |     std::vector<int> hits(5, 0);
210 |     std::vector<int> get_operations(5, 0);
211 |     std::vector<std::string> names = {"LRU", "LFU", "ARC", "LRU-K", "LFU-Aging"};
212 | 
213 |     // 为每种缓存算法运行相同的测试
214 |     for (int i = 0; i < caches.size(); ++i) { 
215 |         // 先预热缓存，只插入少量初始数据
216 |         for (int key = 0; key < 30; ++key) {
217 |             std::string value = "init" + std::to_string(key);
218 |             caches[i]->put(key, value);
219 |         }
220 |         
221 |         // 进行多阶段测试，每个阶段有不同的访问模式
222 |         for (int op = 0; op < OPERATIONS; ++op) {
223 |             // 确定当前阶段
224 |             int phase = op / PHASE_LENGTH;
225 |             
226 |             // 每个阶段的读写比例不同 
227 |             int putProbability;
228 |             switch (phase) {
229 |                 case 0: putProbability = 15; break;  // 阶段1: 热点访问，15%写入更合理
230 |                 case 1: putProbability = 30; break;  // 阶段2: 大范围随机，写比例为30%
231 |                 case 2: putProbability = 10; break;  // 阶段3: 顺序扫描，10%写入保持不变
232 |                 case 3: putProbability = 25; break;  // 阶段4: 局部性随机，微调为25%
233 |                 case 4: putProbability = 20; break;  // 阶段5: 混合访问，调整为20%
234 |                 default: putProbability = 20;
235 |             }
236 |             
237 |             // 确定是读还是写操作
238 |             bool isPut = (gen() % 100 < putProbability);
239 |             
240 |             // 根据不同阶段选择不同的访问模式生成key - 优化后的访问范围
241 |             int key;
242 |             if (op < PHASE_LENGTH) {  // 阶段1: 热点访问 - 热点数量5，使热点更集中
243 |                 key = gen() % 5;
244 |             } else if (op < PHASE_LENGTH * 2) {  // 阶段2: 大范围随机 - 范围400，更适合30大小的缓存
245 |                 key = gen() % 400;
246 |             } else if (op < PHASE_LENGTH * 3) {  // 阶段3: 顺序扫描 - 保持100个键
247 |                 key = (op - PHASE_LENGTH * 2) % 100;
248 |             } else if (op < PHASE_LENGTH * 4) {  // 阶段4: 局部性随机 - 优化局部性区域大小
249 |                 // 产生5个局部区域，每个区域大小为15个键，与缓存大小20接近但略小
250 |                 int locality = (op / 800) % 5;  // 调整为5个局部区域
251 |                 key = locality * 15 + (gen() % 15);  // 每区域15个键
252 |             } else {  // 阶段5: 混合访问 - 增加热点访问比例
253 |                 int r = gen() % 100;
254 |                 if (r < 40) {  // 40%概率访问热点（从30%增加）
255 |                     key = gen() % 5;  // 5个热点键
256 |                 } else if (r < 70) {  // 30%概率访问中等范围
257 |                     key = 5 + (gen() % 45);  // 缩小中等范围为50个键
258 |                 } else {  // 30%概率访问大范围（从40%减少）
259 |                     key = 50 + (gen() % 350);  // 大范围也相应缩小
260 |                 }
261 |             }
262 |             
263 |             if (isPut) {
264 |                 // 执行写操作
265 |                 std::string value = "value" + std::to_string(key) + "_p" + std::to_string(phase);
266 |                 caches[i]->put(key, value);
267 |             } else {
268 |                 // 执行读操作并记录命中情况
269 |                 std::string result;
270 |                 get_operations[i]++;
271 |                 if (caches[i]->get(key, result)) {
272 |                     hits[i]++;
273 |                 }
274 |             }
275 |         }
276 |     }
277 | 
278 |     printResults("工作负载剧烈变化测试", CAPACITY, get_operations, hits);
279 | }
280 | 
281 | int main() {
282 |     testHotDataAccess();
283 |     testLoopPattern();
284 |     testWorkloadShift();
285 |     return 0;
286 | }


--------------------------------------------------------------------------------
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--------------------------------------------------------------------------------
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545 | covered work so as to satisfy simultaneously your obligations under this
546 | License and any other pertinent obligations, then as a consequence you may
547 | not convey it at all.  For example, if you agree to terms that obligate you
548 | to collect a royalty for further conveying from those to whom you convey
549 | the Program, the only way you could satisfy both those terms and this
550 | License would be to refrain entirely from conveying the Program.
551 | 
552 |   13. Use with the GNU Affero General Public License.
553 | 
554 |   Notwithstanding any other provision of this License, you have
555 | permission to link or combine any covered work with a work licensed
556 | under version 3 of the GNU Affero General Public License into a single
557 | combined work, and to convey the resulting work.  The terms of this
558 | License will continue to apply to the part which is the covered work,
559 | but the special requirements of the GNU Affero General Public License,
560 | section 13, concerning interaction through a network will apply to the
561 | combination as such.
562 | 
563 |   14. Revised Versions of this License.
564 | 
565 |   The Free Software Foundation may publish revised and/or new versions of
566 | the GNU General Public License from time to time.  Such new versions will
567 | be similar in spirit to the present version, but may differ in detail to
568 | address new problems or concerns.
569 | 
570 |   Each version is given a distinguishing version number.  If the
571 | Program specifies that a certain numbered version of the GNU General
572 | Public License "or any later version" applies to it, you have the
573 | option of following the terms and conditions either of that numbered
574 | version or of any later version published by the Free Software
575 | Foundation.  If the Program does not specify a version number of the
576 | GNU General Public License, you may choose any version ever published
577 | by the Free Software Foundation.
578 | 
579 |   If the Program specifies that a proxy can decide which future
580 | versions of the GNU General Public License can be used, that proxy's
581 | public statement of acceptance of a version permanently authorizes you
582 | to choose that version for the Program.
583 | 
584 |   Later license versions may give you additional or different
585 | permissions.  However, no additional obligations are imposed on any
586 | author or copyright holder as a result of your choosing to follow a
587 | later version.
588 | 
589 |   15. Disclaimer of Warranty.
590 | 
591 |   THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
596 | PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
597 | IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599 | 
600 |   16. Limitation of Liability.
601 | 
602 |   IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
610 | SUCH DAMAGES.
611 | 
612 |   17. Interpretation of Sections 15 and 16.
613 | 
614 |   If the disclaimer of warranty and limitation of liability provided
615 | above cannot be given local legal effect according to their terms,
616 | reviewing courts shall apply local law that most closely approximates
617 | an absolute waiver of all civil liability in connection with the
618 | Program, unless a warranty or assumption of liability accompanies a
619 | copy of the Program in return for a fee.
620 | 
621 |                      END OF TERMS AND CONDITIONS
622 | 
623 |             How to Apply These Terms to Your New Programs
624 | 
625 |   If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 | 
629 |   To do so, attach the following notices to the program.  It is safest
630 | to attach them to the start of each source file to most effectively
631 | state the exclusion of warranty; and each file should have at least
632 | the "copyright" line and a pointer to where the full notice is found.
633 | 
634 |     <one line to give the program's name and a brief idea of what it does.>
635 |     Copyright (C) <year>  <name of author>
636 | 
637 |     This program is free software: you can redistribute it and/or modify
638 |     it under the terms of the GNU General Public License as published by
639 |     the Free Software Foundation, either version 3 of the License, or
640 |     (at your option) any later version.
641 | 
642 |     This program is distributed in the hope that it will be useful,
643 |     but WITHOUT ANY WARRANTY; without even the implied warranty of
644 |     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
645 |     GNU General Public License for more details.
646 | 
647 |     You should have received a copy of the GNU General Public License
648 |     along with this program.  If not, see <https://www.gnu.org/licenses/>.
649 | 
650 | Also add information on how to contact you by electronic and paper mail.
651 | 
652 |   If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 | 
655 |     <program>  Copyright (C) <year>  <name of author>
656 |     This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657 |     This is free software, and you are welcome to redistribute it
658 |     under certain conditions; type `show c' for details.
659 | 
660 | The hypothetical commands `show w' and `show c' should show the appropriate
661 | parts of the General Public License.  Of course, your program's commands
662 | might be different; for a GUI interface, you would use an "about box".
663 | 
664 |   You should also get your employer (if you work as a programmer) or school,
665 | if any, to sign a "copyright disclaimer" for the program, if necessary.
666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | <https://www.gnu.org/licenses/>.
668 | 
669 |   The GNU General Public License does not permit incorporating your program
670 | into proprietary programs.  If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library.  If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License.  But first, please read
674 | <https://www.gnu.org/licenses/why-not-lgpl.html>.
675 | 


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