├── .gitignore
├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── push-rules.txt
├── 【DSA】数据结构与算法（C语言版本）
├── 01 绪论与概要.md
├── 02 顺序表.md
├── 03 单链表.md
├── 04 双链表、循环链表与静态链表.md
├── 05 链表逆置.md
├── 06 栈与栈的应用.md
├── 07 队列与队列的应用.md
├── 08 串.md
├── 09 串的模式匹配 -- BF与KMP.md
├── 10 树与二叉树.md
├── 11 二叉树遍历.md
├── 12 二叉树线索化.md
├── 13 树和森林的遍历.md
├── 14 哈夫曼编码、并查集.md
├── 15 二叉排序树BST与平衡二叉树AVL.md
├── 16 红黑树.md
├── 17 B树、B+树.md
├── 18 图与图的存储方式.md
├── 19 图的基本操作.md
├── 20 图的最短路径问题.md
├── 21 图的拓扑排序和关键路径.md
├── 22 顺序查找、二分查找.md
├── 23 分块查找、散列查找（哈希查找）.md
├── 24 C语言的哈希实现 uthash库.md
├── 25 排序算法概要、冒泡排序.md
├── 26 插入排序.md
├── 27 希尔排序.md
├── 28 快速排序.md
├── 29 选择排序.md
├── 30 堆与堆排序.md
├── 31 归并排序.md
├── 32 基数排序.md
├── 33 外部排序、败者树.md
├── 34 常用算法 - 单调栈.md
├── 35 常用算法 - 单调栈.md
├── 36 常用算法 - 贪心.md
├── 37 常用算法 - 前缀和.md
├── 38 常用算法 - 分治.md
├── 39 常用算法 - 回溯法.md
├── 40 常用算法 - 动态规划.md
├── README.md
├── img
│ ├── 01_prefix
│ │ ├── 01 世界是结构的.jpg
│ │ ├── 02 DSA位于什么位置.jpg
│ │ ├── 03 数据描述世界.jpg
│ │ ├── 04 数据的逻辑结构.jpg
│ │ ├── 05 常见抽象数据结构.jpg
│ │ ├── 06 数据结构和算法的关系.jpg
│ │ ├── 07 大O计算法.jpg
│ │ ├── 08 常见数据结构操作复杂度.jpg
│ │ └── Obsidian.png
│ ├── 02_linear_list
│ │ ├── 01 线性表.jpg
│ │ ├── 02 是否传引用&的区别.jpg
│ │ ├── 03 顺序表的动态扩充.jpg
│ │ ├── 04 顺序表的增加数据.jpg
│ │ ├── 05 顺序表插入例外情况.jpg
│ │ ├── 06 顺序表的删除数据.jpg
│ │ ├── 07 顺序表查找.jpg
│ │ ├── 08 单链表.jpg
│ │ ├── 09 顺序表 Vs 链表.jpg
│ │ ├── 10 单链表的结点.jpg
│ │ ├── 11 链表的初始化 是否带头结点.jpg
│ │ ├── 12 链表插入 给定位序 1.jpg
│ │ ├── 13 链表插入 给定位序 2.jpg
│ │ ├── 14 链表插入 某个指定结点后插元素.jpg
│ │ ├── 15 链表插入 某个指定结点前插元素 常规.jpg
│ │ ├── 16 链表插入 某个指定结点前插元素 Swap.jpg
│ │ ├── 17 链表删除 给定位序1.JPG
│ │ ├── 18 链表删除 给定位序2.jpg
│ │ ├── 19 链表删除 给定结点 交换数据.JPG
│ │ ├── 20 单链表尾插法.JPG
│ │ ├── 21 单链表头插法.JPG
│ │ ├── 22 单链表与双链表.JPG
│ │ ├── 23 双链表结点.jpg
│ │ ├── 24 双链表初始化 带头结点的双链表.JPG
│ │ ├── 25 双链表插入 1.JPG
│ │ ├── 26 双链表插入 2.JPG
│ │ ├── 27 双链表删除.JPG
│ │ ├── 28 循环单链表.JPG
│ │ ├── 29 循环单链表 空表.jpg
│ │ ├── 30 循环双链表.JPG
│ │ ├── 31 循环双链表 空表.jpg
│ │ ├── 32 静态链表与单链表.JPG
│ │ ├── 33 逆置链表.JPG
│ │ ├── 34 迭代法逆置链表.JPG
│ │ ├── 35 迭代法逆置链表.JPG
│ │ ├── 36 迭代法逆置链表.JPG
│ │ ├── 37 迭代法逆置链表.JPG
│ │ ├── 38 迭代法逆置链表.JPG
│ │ ├── 39 头插法法逆置链表.JPG
│ │ ├── 40 头插法法逆置链表.JPG
│ │ ├── 41 头插法法逆置链表.JPG
│ │ ├── 42 原地逆置法.JPG
│ │ ├── 43 原地逆置法.JPG
│ │ ├── 44 原地逆置法.JPG
│ │ ├── 45 原地逆置法.JPG
│ │ ├── 46 递归逆置法.JPG
│ │ ├── 47 递归逆置法.JPG
│ │ └── 48 递归逆置法.JPG
│ ├── 03_stack_queue
│ │ ├── 01 栈.JPG
│ │ ├── 02 顺序栈.JPG
│ │ ├── 03 入栈.JPG
│ │ ├── 04 出栈.JPG
│ │ ├── 05 共享栈，双向生长.JPG
│ │ ├── 06 链栈-入栈.jpg
│ │ ├── 07 链栈-出栈.jpg
│ │ ├── 08 括号匹配的场景.jpg
│ │ ├── 09 括号匹配算法演示.jpg
│ │ ├── 10 中缀表达式转后缀表达式.JPG
│ │ ├── 11 左优先 保证算法的唯一性.JPG
│ │ ├── 12 中缀表达式转前缀表达式.jpg
│ │ ├── 13 右优先 保证算法一致.jpg
│ │ ├── 14 函数调用栈.jpg
│ │ ├── 15 斐波拉契数列递归.jpg
│ │ ├── 16 队列.jpg
│ │ ├── 17 顺序存储队列.jpg
│ │ ├── 18 顺序队列初始化和判空.jpg
│ │ ├── 19 入队.jpg
│ │ ├── 20 循环队列.jpg
│ │ ├── 21 满队列.jpg
│ │ ├── 22 出队.jpg
│ │ ├── 23 链式队列.jpg
│ │ ├── 24 链式队列初始化.jpg
│ │ ├── 25 入队链式队列.jpg
│ │ ├── 26 出队链式队列.jpg
│ │ └── 27 双端队列.jpg
│ ├── 04_string
│ │ ├── 01 字符串.jpg
│ │ ├── 02 主串和子串.jpg
│ │ ├── 03 数组表示字符串.jpg
│ │ ├── 04 链表表示串.jpg
│ │ ├── 05 求子串.jpg
│ │ ├── 06 串比较.jpg
│ │ ├── 07 串的模式匹配.jpg
│ │ ├── 08 朴素模式匹配算法 匹配失败.jpg
│ │ ├── 09 朴素模式匹配算法 步数分析.jpg
│ │ ├── 10 朴素模式匹配算法 匹配成功.jpg
│ │ ├── 11 模式匹配的最坏情况.jpg
│ │ ├── 12 模式匹配的最好情况.jpg
│ │ ├── 13 子串匹配失败但前若干个匹配成功.jpg
│ │ ├── 14 主串不移位置 子串移至指定位置.jpg
│ │ ├── 15 第6个元素匹配失败.jpg
│ │ ├── 16 第5个元素匹配失败.jpg
│ │ ├── 17 第4个元素匹配失败.jpg
│ │ ├── 18 第3个元素匹配失败.jpg
│ │ ├── 19 第2个元素匹配失败.jpg
│ │ ├── 20 第1个元素匹配失败.jpg
│ │ ├── 21 KMP演示1.jpg
│ │ ├── 22 KMP演示2.jpg
│ │ ├── 23 KMP演示3.jpg
│ │ ├── 24 google next[1]next[2].jpg
│ │ ├── 25 google next[3].jpg
│ │ ├── 26 google next[4].jpg
│ │ ├── 27 google next[5].jpg
│ │ ├── 28 google next[6].jpg
│ │ ├── 29 PMT引导KMP算法匹配.jpg
│ │ ├── 30 求next数组1.jpg
│ │ └── 31 求next数组2.jpg
│ ├── 05_tree_part_1
│ │ ├── 01 树.jpg
│ │ ├── 02 子树.jpg
│ │ ├── 03 树的高度和结点的度.jpg
│ │ ├── 04 森林.jpg
│ │ ├── 05 树的度和n叉树.jpg
│ │ ├── 06 度为3的树.jpg
│ │ ├── 07 树的度和n叉树2.jpg
│ │ ├── 08 左子树和右子树.jpg
│ │ ├── 09 二叉树左右子树的状态.jpg
│ │ ├── 10 满二叉树和完全二叉树.jpg
│ │ ├── 11 二叉搜索树.jpg
│ │ ├── 12 二叉平衡树与非二叉平衡树AVL.jpg
│ │ ├── 13 二叉树结点数量的规律.jpg
│ │ ├── 14 完全二叉树结点数量关系.jpg
│ │ ├── 15 二叉树顺序存储 完全二叉树.jpg
│ │ ├── 16 二叉树顺序存储 非完全二叉树.jpg
│ │ ├── 17 二叉树顺序存储 非完全二叉树最坏情况.jpg
│ │ ├── 18 链式存储树.jpg
│ │ ├── 19 空树和非空树.jpg
│ │ ├── 20 三种遍历.jpg
│ │ ├── 21 前序遍历.jpg
│ │ ├── 22 中序遍历.jpg
│ │ ├── 23 后序遍历.jpg
│ │ ├── 24 层序遍历.jpg
│ │ ├── 25 中序遍历构建二叉树.jpg
│ │ ├── 26 前序遍历构建二叉树.jpg
│ │ ├── 27 后序遍历构建二叉树.jpg
│ │ ├── 28 层序遍历构建二叉树.jpg
│ │ ├── 29 前序+中序 框架.jpg
│ │ ├── 30 前序+中序 还原 1.jpg
│ │ ├── 31 前序+中序 还原 2.jpg
│ │ ├── 32 前序+中序 还原 3.jpg
│ │ ├── 33 前序+中序 还原 4.jpg
│ │ ├── 34 后序+中序 框架.jpg
│ │ ├── 35 后序+中序 还原 1.jpg
│ │ ├── 36 后序+中序 还原 2.jpg
│ │ ├── 37 后序+中序 还原 3.jpg
│ │ ├── 38 后序+中序 还原 4.jpg
│ │ ├── 39 后序+中序 还原 5.jpg
│ │ ├── 40 层序+中序 框架.jpg
│ │ ├── 41 层序+中序 还原 1.jpg
│ │ ├── 42 层序+中序 还原 2.jpg
│ │ ├── 43 层序+中序 还原 3.jpg
│ │ ├── 44 层序+中序 还原 4.jpg
│ │ ├── 45 层序+中序 还原 5.jpg
│ │ ├── 46 层序+中序 还原 6.jpg
│ │ ├── 47 两种遍历构造唯一二叉树.jpg
│ │ └── 48 无法确定二叉树结构.jpg
│ ├── 05_tree_part_2
│ │ ├── 49 数据非线性转线性.jpg
│ │ ├── 50 线性化前驱后继关系变化.jpg
│ │ ├── 51 指定结点遍历序列.jpg
│ │ ├── 52 二叉树中序遍历寻找前驱.jpg
│ │ ├── 53 二叉树中序遍历寻找后继.jpg
│ │ ├── 54 线索二叉树.jpg
│ │ ├── 55 二叉树线索化.jpg
│ │ ├── 56 先序遍历线索二叉树.jpg
│ │ ├── 57 后序遍历线索二叉树.jpg
│ │ ├── 58 中序遍历线索二叉树.jpg
│ │ ├── 59 中序遍历线索二叉树,左右孩子存在,求其后继.jpg
│ │ ├── 60 中序遍历线索二叉树,左右孩子存在,求其前驱.jpg
│ │ ├── 61 先序遍历线索二叉树,左右孩子存在,求其后继.jpg
│ │ ├── 62 先序遍历线索二叉树,左右孩子存在,求其前驱.jpg
│ │ ├── 63 后序遍历线索二叉树,左右孩子存在,求其前驱.jpg
│ │ ├── 64 后序遍历线索二叉树,左右孩子存在,求其后继.jpg
│ │ ├── 70 孩子表示法.jpg
│ │ ├── 71 树转化成二叉树.jpg
│ │ ├── 72 森林转化成二叉树.jpg
│ │ ├── 73 哈夫曼树.jpg
│ │ ├── 74 哈夫曼树生成.jpg
│ │ ├── 75 哈夫曼树生成2.jpg
│ │ ├── 76 哈夫曼编码.jpg
│ │ ├── 77 哈夫曼编码前缀编码.jpg
│ │ ├── 78 集合与子集.jpg
│ │ ├── 79 集合转化成森林.jpg
│ │ ├── 80 集合合并.jpg
│ │ ├── 81 并查集数组实现存储.jpg
│ │ ├── 82 并查集的初始化.jpg
│ │ ├── 83 并查集查找.jpg
│ │ ├── 84 并查集合并.jpg
│ │ ├── 85 并查集查找复杂度.jpg
│ │ ├── 86 并查集合并-小树合并入大树.jpg
│ │ └── 87 并查集压缩路径.jpg
│ ├── 05_tree_part_3
│ │ ├── 100 调整最小不平衡子树_LL.jpg
│ │ ├── 101 调整最小不平衡子树_RR.jpg
│ │ ├── 102 调整最小不平衡子树_LR_1.JPG
│ │ ├── 103 调整最小不平衡子树_LR_2.JPG
│ │ ├── 104 调整最小不平衡子树_LR_3.JPG
│ │ ├── 105 调整最小不平衡子树_RL_1.JPG
│ │ ├── 106 调整最小不平衡子树_RL_2.JPG
│ │ ├── 107 调整最小不平衡子树_RL_3.JPG
│ │ ├── 108 RBT.jpg
│ │ ├── 109 BH.jpg
│ │ ├── 110 红黑树结点最少情况.jpg
│ │ ├── 111 RBT插入.jpg
│ │ ├── 112 RBT插入情形2.jpg
│ │ ├── 113 RBT插入情形3.jpg
│ │ ├── 114 RBT插入情形4.jpg
│ │ ├── 115 RBT插入情形5.jpg
│ │ ├── 116 RBT插入情形5.jpg
│ │ ├── 88 二叉排序树BST.jpg
│ │ ├── 89 二叉排序树查找.jpg
│ │ ├── 90 二叉排序树构造.jpg
│ │ ├── 91 BST的删除1.jpg
│ │ ├── 92 BST的删除2.jpg
│ │ ├── 93 BST的删除3.jpg
│ │ ├── 94 BST的删除4.jpg
│ │ ├── 95 二叉排序树查找成功ASL.jpg
│ │ ├── 96 二叉排序树查找失败ASL.jpg
│ │ ├── 97 AVL 二叉平衡树.jpg
│ │ ├── 98 BST插入导致平衡树变成非平衡.jpg
│ │ └── 99 最小不平衡子树.jpg
│ ├── 05_tree_part_4
│ │ ├── B树删除-前驱替代.jpg
│ │ ├── B树删除-后继替代.jpg
│ │ ├── b+树.jpg
│ │ ├── b+树的平衡.jpg
│ │ ├── b+树的查找.jpg
│ │ ├── b树.jpg
│ │ ├── b树插入.jpg
│ │ ├── b树插入2.jpg
│ │ ├── b树插入3.jpg
│ │ ├── 不平衡的B树查找效率.jpg
│ │ ├── 五叉排序树.jpg
│ │ ├── 五叉树的查找效率.jpg
│ │ ├── 平衡的B树查找效率.jpg
│ │ └── 根节点只有两个.jpg
│ ├── 06_map
│ │ ├── 01 图.jpg
│ │ ├── 02 中国高铁网络.jpg
│ │ ├── 03 社交媒体网络图.jpg
│ │ ├── 04 有向图无向图.png
│ │ ├── 05 简单图多重图.png
│ │ ├── 06 连通图强连通图.png
│ │ ├── 07 连通分量.png
│ │ ├── 08 有向图强连通分量.png
│ │ ├── 09 邻接矩阵法.png
│ │ ├── 10 邻接矩阵带权图.png
│ │ ├── 11 邻接表表示不唯一.png
│ │ ├── 12 十字链表.png
│ │ └── 13 邻接多重表.png
│ ├── 07_search
│ │ ├── 01 顺序查找.jpg
│ │ ├── 02 顺序查找成功 哨兵模式.jpg
│ │ ├── 03 顺序查找失败 哨兵模式.jpg
│ │ ├── 04 查找判定树.jpg
│ │ ├── 05 概率不同的查找.jpg
│ │ ├── 06 二分查找1.jpg
│ │ ├── 07 二分查找2.jpg
│ │ ├── 08 二分查找3.jpg
│ │ ├── 09 二分查找4.jpg
│ │ ├── 10 二分查找成功判定树.jpg
│ │ ├── 11 二分查找失败判定树.jpg
│ │ ├── 12 判定树构造.jpg
│ │ ├── 13 索引表.jpg
│ │ ├── 14 散列表.jpg
│ │ ├── 15 拉链法.jpg
│ │ ├── 16 除留余数法用质数.jpg
│ │ ├── 17 直接定址法.jpg
│ │ ├── 18 数字分析法.jpg
│ │ ├── 19 平方取中法.jpg
│ │ ├── 20 线性探测法.jpg
│ │ ├── 21 Hashmap.jpg
│ │ ├── 22 Key-Value Pair.jpg
│ │ ├── 23 HashTbl逻辑结构.jpg
│ │ ├── 24 HashTbl查找.jpg
│ │ ├── 25 HashTbl插入.jpg
│ │ └── 26 HashTbl删除.jpg
│ ├── 08_sort
│ │ ├── 01 十大排序.jpg
│ │ ├── 02 排序的稳定性.jpg
│ │ ├── 03 内部排序 VS 外部排序.jpg
│ │ ├── 04 冒泡排序0.jpg
│ │ ├── 05 冒泡排序1.jpg
│ │ ├── 06 冒泡排序2.jpg
│ │ ├── 07 冒泡排序3.jpg
│ │ ├── 08 冒泡排序4.jpg
│ │ ├── 09 冒泡排序5.jpg
│ │ ├── 10 冒泡排序6.jpg
│ │ ├── 11 插入排序.jpg
│ │ ├── 12 插入排序.jpg
│ │ ├── 13 插入排序.jpg
│ │ ├── 14 插入排序.jpg
│ │ ├── 15 插入排序.jpg
│ │ ├── 16 插入排序.jpg
│ │ ├── 17 插入排序.jpg
│ │ ├── 18 插入排序 带哨兵模式.jpg
│ │ ├── 19 插入排序-使用二分查找.jpg
│ │ ├── 20 插入排序-使用二分查找.jpg
│ │ ├── 21 插入排序-使用二分查找.jpg
│ │ ├── 22 插入排序-使用二分查找.jpg
│ │ ├── 23 希尔排序.jpg
│ │ ├── 24 希尔排序 演示1.jpg
│ │ ├── 25 希尔排序 演示2.jpg
│ │ ├── 26 希尔排序 演示3.jpg
│ │ ├── 27 希尔排序 演示4.jpg
│ │ ├── 28 快速排序.jpg
│ │ ├── 29 快速排序2.jpg
│ │ ├── 30 快速排序3.jpg
│ │ ├── 31 快速排序4.jpg
│ │ ├── 32 快速排序5.jpg
│ │ ├── 33 快速排序6.jpg
│ │ ├── 34 快速排序7.jpg
│ │ ├── 35 快速排序转化二叉树.jpg
│ │ ├── 36 快速排序的调用栈.jpg
│ │ ├── 37 快速排序的调用栈2.jpg
│ │ ├── 38 快速排序的调用栈3.jpg
│ │ ├── 39 快速排序的调用栈4.jpg
│ │ ├── 40 快速排序的调用栈5.jpg
│ │ ├── 41 快速排序的调用栈6.jpg
│ │ ├── 42 快速排序的调用栈7.jpg
│ │ ├── 43 快速排序的调用栈8.jpg
│ │ ├── 44 快速排序的调用栈9.jpg
│ │ ├── 45 快速排序的调用栈10.jpg
│ │ ├── 46 快速排序的调用栈11.jpg
│ │ ├── 47 快速排序的调用栈12.jpg
│ │ ├── 50 快速排序的不稳定性.jpg
│ │ ├── 50 简单选择排序1.jpg
│ │ ├── 51 简单选择排序2.jpg
│ │ ├── 52 简单选择排序3.jpg
│ │ ├── 53 简单选择排序4.jpg
│ │ ├── 54 堆.jpg
│ │ ├── Bubble_sort_animation.gif
│ │ ├── heap_sort.gif
│ │ ├── insertion_sort.gif
│ │ ├── merge_sort.gif
│ │ ├── quick_sort.gif
│ │ ├── selection_sort.gif
│ │ └── shell_sort.gif
│ └── 09_other_algorithm
│ │ └── 全排列 回溯算法.png
└── src
│ ├── graph
│ ├── BFS.c
│ ├── DFS.c
│ ├── adjacency_list.h
│ ├── adjacency_matrix.h
│ ├── adjacency_multi_list.h
│ └── orthogonal_linked_list.h
│ ├── search
│ ├── binary_search.c
│ └── uthash
│ │ ├── example.c
│ │ └── uthash.h
│ ├── sort
│ ├── bubble_sort.c
│ ├── heap_sort.c
│ ├── insert_sort.c
│ ├── quick_sort.c
│ └── shell_sort.c
│ ├── string
│ ├── pattern_matching_bf.c
│ └── pattern_matching_kmp.c
│ └── tree
│ ├── tree_in_order.c
│ ├── tree_in_order_get_predecessor.c
│ ├── tree_in_order_get_successor.c
│ ├── tree_level_order.c
│ ├── tree_post_order.c
│ └── tree_pre_order.c
├── 【NET】计算机网络
└── 01 计算机网络基础知识.md
├── 【OS】操作系统
├── 41 操作系统概要、功能特征与发展演变.md
├── 42 操作系统运行机制、中断与异常、系统调用、体系结构.md
├── 43 进程管理1-进程切换、进程组织和管理.md
├── 44 进程管理2-进程间通信、多线程.md
├── 45 进程管理3-进程调度.md
├── 46 进程管理4-调度算法.md
├── 47 进程管理5-进程互斥、进程同步机制.md
├── 48 进程管理6-生产者与消费者问题.md
├── 49 进程管理7-死锁.md
├── 50 内存管理1-覆盖、交换、内存分配.md
├── 51 内存管理2-分页存储.md
├── 52 内存管理3-分段存储.md
├── 53 文件管理1-逻辑结构和物理结构.md
├── 54 文件管理2-文件操作与层次结构.md
├── 55 IO 管理1-IO系统组成.md
├── 56 IO 管理2-设备与磁盘管理.md
├── README.md
└── img
│ ├── 01_prefix
│ ├── 00 Linux系统内核的组成.jpg
│ ├── 01 任务管理器.jpg
│ ├── 02 计算机系统架构与操作系统.jpg
│ ├── 03 封装.jpg
│ ├── 04 bat文件批处理.jpg
│ ├── 05 命令行交互式系统.jpg
│ ├── 06 GUI.jpg
│ ├── 07 系统调用.jpg
│ ├── 08 系统调用_printf.jpg
│ ├── 09 OS的功能和目标.jpg
│ ├── 10 并发和并行.jpg
│ ├── 11 并发和并行.jpg
│ ├── 12 多处理器.jpg
│ ├── 13 多处理操作系统.jpg
│ ├── 14 虚拟化技术.jpg
│ ├── 15 同步和异步.jpg
│ ├── 16 手工阶段.jpg
│ ├── 17 批处理阶段.jpg
│ ├── 18 批处理.jpg
│ ├── 19 单道批处理和多道批处理.jpg
│ ├── 20 分时和实时OS.jpg
│ ├── 21 Unix_history-simple.png
│ ├── 22 Android_Linux.jpg
│ ├── 23 how_code_run.jpg
│ ├── 24 应用与内核.jpg
│ ├── 25 docker.jpg
│ ├── 26 GUI.jpg
│ ├── 27 内核态和用户态.jpg
│ ├── 28 状态切换.jpg
│ ├── 29 中断和异常.jpg
│ ├── 30 中断在做饭上体现.jpg
│ ├── 31 忙等待与轮询.jpg
│ ├── 32 中断.jpg
│ ├── 33 中断类型.jpg
│ ├── 34 切菜的中断.jpg
│ ├── 35 中断向量表.jpg
│ ├── 36 系统调用.jpg
│ ├── 37 系统调用与库函数关系.jpg
│ ├── 38 系统调用的过程.jpg
│ ├── 39 计算机系统层次结构.jpg
│ ├── 40 微内核和宏内核.jpg
│ ├── 41 Linux_Kernel.png
│ ├── 42 Windows内核.jpg
│ ├── Real-Time-Operating-System.png
│ ├── Time-Sharing-System-In-OS.png
│ └── sync-vs-async-schema.png
│ ├── 02_process_mngmnt
│ ├── 01 计算机系统的抽象.jpg
│ ├── 02 PID.jpg
│ ├── 03 PCB.jpg
│ ├── 04 程序段和数据段.jpg
│ ├── 05 进程双状态模型.jpg
│ ├── 06 进程五状态模型.jpg
│ ├── 07 进程七状态模型.jpg
│ ├── 08 进程组织-索引.jpg
│ ├── 08 进程组织-链接.jpg
│ ├── 09 原语.jpg
│ ├── 10 原语具备原子性.jpg
│ ├── 11 开中断和关中断.jpg
│ ├── 12 程序指令.jpg
│ ├── 13 IPC.jpg
│ ├── 14 共享内存.jpg
│ ├── 15 消息传递.jpg
│ ├── 16 管道通信.jpg
│ ├── 17 单线程和多线程.jpg
│ ├── 18 多线程进程.jpg
│ ├── 19 用户级多线程.jpg
│ ├── 20 内核级别线程.jpg
│ ├── 21 内核级别线程.jpg
│ ├── 22 调度的例子.jpg
│ ├── 23 三级调度.jpg
│ ├── 24 高级调度.jpg
│ ├── 25 低级调度.jpg
│ ├── 26 中级调度.jpg
│ ├── 27 进程调度发生场景.jpg
│ ├── 28 进程调度不会发生场景.jpg
│ ├── 29 临界区.jpg
│ ├── 30 抢占式和非抢占式.jpg
│ ├── 31 上下文切换.jpg
│ ├── 32 周转时间.jpg
│ ├── 33 等待时间.jpg
│ ├── 34 FCFS 先来先服务算法.jpg
│ ├── 35 短进程优先算法.jpg
│ ├── 36 最短剩余时间优先.jpg
│ ├── 37 高响应比优先.jpg
│ ├── 38 时间片轮转算法.jpg
│ ├── 39 时间片轮转算法.jpg
│ ├── 40 时间片轮转算法.jpg
│ ├── 41 优先级调度算法.jpg
│ ├── 43 优先级调度算法.jpg
│ ├── 44 多级反馈队列算法.jpg
│ ├── 45 Dijkstra.jpg
│ ├── 46 临界资源问题.jpg
│ ├── 47 临界资源.jpg
│ ├── 48 打印机资源的互斥.jpg
│ ├── 49 信号量.jpg
│ ├── 50 记录型信号量.jpg
│ ├── 51 互斥锁mutex.jpg
│ ├── 52 互斥锁mutex实现进程同步.jpg
│ ├── 53 生产者-消费者模式.jpg
│ ├── 54 生产者-消费者模式解释.jpg
│ ├── 55 多生产者多消费者.jpg
│ ├── 56 PV-多生产多消费.jpg
│ ├── 57 吸烟者问题.jpg
│ ├── 58 吸烟者问题.jpg
│ ├── 59 读者写者问题.jpg
│ ├── 60 哲学家进餐问题.jpg
│ ├── 61 管程.jpg
│ └── 62 死锁.jpg
│ ├── 03_memory_mngmnt
│ ├── 01 存储的分层架构.jpg
│ ├── 02 内存剖析.jpg
│ ├── 03 逻辑地址和物理地址.jpg
│ ├── 04 程序装载.jpg
│ ├── 05 程序执行过程.jpg
│ ├── 06 内存保护.jpg
│ ├── 07 覆盖.jpg
│ ├── 08 覆盖技术的例子.jpg
│ ├── 09 交换技术.jpg
│ ├── 11 七状态进程模型.jpg
│ ├── 12 连续分配内存.jpg
│ ├── 13 动态分区内存.jpg
│ ├── 14 空闲分区表.jpg
│ ├── 15 内部碎片.jpg
│ ├── 16 外部碎片.jpg
│ ├── 17 内存压缩.jpg
│ ├── 18 首次适应算法.jpg
│ ├── 19 首次适应算法.jpg
│ ├── 20 首次适应算法.jpg
│ ├── 21 最佳适应算法.jpg
│ ├── 22 最佳适应算法.jpg
│ ├── 23 最佳适应算法.jpg
│ ├── 24 最坏适应算法.jpg
│ ├── 25 最坏适应算法.jpg
│ ├── 26 最坏适应算法.jpg
│ ├── 27 邻接适应算法.jpg
│ ├── 28 页.jpg
│ ├── 29 页表.jpg
│ ├── 30 逻辑地址.jpg
│ ├── 31 逻辑地址转化物理地址.jpg
│ ├── 32 分页地址转换.jpg
│ ├── 32 快表.jpg
│ ├── 33 TLB.jpg
│ ├── 34 二级页表.jpg
│ ├── 35 二级页表的地址转换.jpg
│ ├── 36 虚拟内存.jpg
│ ├── 37 缺页中断.jpg
│ ├── 38 分段.jpg
│ ├── 39 处理机视角的分段寻址.jpg
│ ├── 40 段寄存器.jpg
│ ├── 41 分段地址变换.jpg
│ ├── 42 分段分页区别.jpg
│ ├── 43 段页式.jpg
│ ├── 44 段页式三次访存.jpg
│ ├── 44 段页式段表和页表.jpg
│ ├── 45 虚拟内存.jpg
│ ├── 46 虚拟内存和物理内存的映射.jpg
│ ├── 47 请求分页存储管理.jpg
│ ├── 48 请求分页的存储管理的页表.jpg
│ ├── 49 请求分页存储管理.jpg
│ ├── 50 页面置换.jpg
│ ├── 51 最佳置换.jpg
│ ├── 52 先进先出.jpg
│ ├── 53 最近最久未使用.jpg
│ ├── 54 驻留集.jpg
│ └── 55 抖动.jpg
│ ├── 04_file_mngmnt
│ ├── 01 文件基本属性.jpg
│ ├── 02-文件间组织关系.jpg
│ ├── 03 磁盘块.jpg
│ ├── 04 索引表.jpg
│ ├── 05 文件路径.jpg
│ ├── 06 FCB.jpg
│ ├── 07 文件路径演化.jpg
│ ├── 08 连续文件分配.jpg
│ ├── 09 链式文件分配.jpg
│ ├── 10 文件分配表.jpg
│ ├── 11 索引文件分配.jpg
│ ├── 12 文件描述符与打开文件描述符.jpg
│ ├── 13 软链接和硬链接.jpg
│ ├── 14 文件系统层次架构.jpg
│ └── 15 VFS架构.jpg
│ └── 05_io_mngmnt
│ ├── 1 IO系统.jpg
│ ├── 2 IO管理器.jpg
│ ├── 3 IO处理逻辑.jpg
│ └── 4 外设处理逻辑.jpg
└── 工具链
└── Cmake
├── Cmake工具使用.md
└── src
├── .gitignore
└── ProjDemo
├── CMakeLists.txt
└── main.cpp
/.gitignore:
--------------------------------------------------------------------------------
1 | .obsidian
2 | .vscode
3 | .vault-stats
4 | *.exe
5 |
--------------------------------------------------------------------------------
/CONTRIBUTING.md:
--------------------------------------------------------------------------------
1 |
2 | 💡 任何对 `CS-Basic-408` 相关知识感兴趣的均可为本仓库贡献、修改，期望共同加入。
3 | ✅ 如果发现有任何错误地方，欢迎指正。
4 |
5 |
6 | 修改递交请表述清楚修改点。
7 | commit格式参考：
8 | ```shell
9 | git commit -m "【修改描述】..."
10 | ```
11 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
1 | MIT License
2 |
3 | Copyright (c) 2023 Liumeng
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
--------------------------------------------------------------------------------
/push-rules.txt:
--------------------------------------------------------------------------------
1 | git add .
2 | git commit -m "【修改描述】..."
3 | git push
4 |
5 |
6 | # 查询字数
7 | cat *.md | wc -m
8 |
9 | # 查询行数
10 | cat *.md | wc -l
11 |
12 | # 查找图片数量
13 | find -name "*.JPG" -o -name "*.jpg" | wc -l
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/20 图的最短路径问题.md:
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1 | #数据结构 #算法 #C
2 | # [73] 最短路径问题——BFS算法
3 |
4 | # [74] 最短路径问题——Dijkstra算法
5 |
6 | # [75] 最短路径问题——Floyd算法
7 |
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/【DSA】数据结构与算法（C语言版本）/21 图的拓扑排序和关键路径.md:
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1 | #数据结构 #算法 #C
2 | # [76] 有向无环图描述表达式
3 |
4 | # [77] 拓扑排序
5 |
6 | # [78] 关键路径
7 |
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/【DSA】数据结构与算法（C语言版本）/27 希尔排序.md:
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1 | #数据结构 #算法 #C
2 | # [85] 希尔排序（Shell Sort）
3 | 也称递减增量排序算法，是插入排序的一种更高效的改进版本。按其设计者希尔（Donald Shell）的名字命名，该算法由1959年公布。希尔排序是非稳定排序算法。
4 | 希尔排序是基于插入排序的以下两点性质而提出改进方法的：
5 | 1. 插入排序在对几乎已经排好序的数据操作时，效率高，即可以达到线性排序的效率；
6 | 2. 但插入排序一般来说是低效的，因为插入排序每次只能将数据移动一位。
7 | ## 1. 算法思想
8 | 希尔排序：先追求表中元素部分有序，再逐渐逼近全局有序。
9 |
10 | 
11 |
12 | 对于插入排序而言，如果原本的表中元素基本有序的话，那采用直接插入排序会达到一个相应不错的效率。
13 | 具体方法：
14 | 先将待排序表分割成若干形如 $L[ i, i + d, i + 2d,…, i + kd ]$ 的“特殊”⼦表，对各个⼦表分别进行直接插入排序。缩小增量 $d$，重复上述过程，直到 $d = 1$ 为⽌。
15 | ## 2. 算法过程
16 | 
17 | 
18 | 
19 | 
20 |
21 | d的值从表长开始，每一轮d值折半。
22 |
23 | ## 3. 算法实现
24 | 以`{50, 60, 61, 70, 80, 61, 83, 88, 87, 99}`表排序为例。
25 | ```c
26 | // 希尔排序
27 | void shellSort(int array[],int n){
28 | // d是元素的增量，
29 | int d, i, j;
30 |
31 | // array[0]是暂存单元，不是哨兵，当j <= 0时,插入位置已到
32 | for (d = n/2; d >= 1; d = d/2) { // 控制步长
33 | for (i = d + 1; i <= n; ++i){
34 | if (array[i] <= array[i - d]){ // 需要将array[i]插入有序增量子表
35 | array[0] = array[i]; // 暂存在array[0]
36 | for (j = i-d; j > 0 && array[0] < array[j]; j -= d){
37 | array[j + d] = array[j]; // 记录后移
38 | }
39 | array[j + d] = array[0]; // 插入
40 | }
41 | }
42 | }
43 | }
44 | ```
45 |
46 | 动画演示：
47 | #未完待续
48 |
49 | 
50 |
51 | ## 4. 算法性能分析
52 | - 空间复杂度： $O(1)$
53 | - 时间间复杂度：和增量序列 $d_1, d_2, d_3 …$ 的选择有关，⽬前⽆法⽤数学⼿段证明确切的时间复杂度。
54 | - 最坏时间复杂度为 $O(N^2)$ ，当 $n$ 在某个特定条件下，可以保证性能提升到至 $O(nlog^2n)$。
55 | - 稳定性：不稳定的排序算法
56 | - 适⽤性：仅适⽤于顺序表，不适⽤于链表。
57 |
58 |
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/【DSA】数据结构与算法（C语言版本）/29 选择排序.md:
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1 | #数据结构 #算法 #C
2 | # [87] 简单选择排序
3 | 选择排序（Selection sort），是一种简单直观的排序算法。它的工作原理如下：
4 | - 首先在未排序序列中找到最小（大）元素，存放到排序序列的起始位置，
5 | - 然后，再从剩余未排序元素中继续寻找最小（大）元素，
6 | - 然后放到已排序序列的末尾。
7 | - 以此类推，直到所有元素均排序完毕。
8 |
9 | 选择排序的主要优点与数据移动有关。如果某个元素位于正确的最终位置上，则它不会被移动。选择排序每次交换一对元素，它们当中**至少有一个将被移到其最终位置上**，因此对`n`个元素的表进行排序总共进行至多`(n-1)`次交换。在所有的完全依靠交换去移动元素的排序方法中，选择排序属于非常好的一种。
10 |
11 | 
12 |
13 | 其中，选择排序又分为**简单选择排序**和**堆排序**。不作特殊说明，以下称简单选择排序为选择排序。
14 | ## 1. 算法思想
15 | 每⼀趟在待排序元素中选取关键字最小的元素加⼊有序子序列。
16 | ## 2. 算法过程
17 | n个记录的直接选择排序可经过`(n-1)`趟直接选择排序得到有序结果。
18 | 具体算法描述如下：
19 |
20 | - 初始状态：无序区为 $R[1…n]$ ，有序区为空；
21 | - 第 $i$ 趟排序: $(i=1,2,3…n-1)$ 开始时，当前有序区和无序区分别为 $R[1…i-1]$ 和 $R(i…n)$。
22 | - 该趟排序，从当前无序区中选出关键字最小的记录 $R[k]$ ，将它与无序区的第1个记录 $R$ 交换，使 $R[1…i]$ 和 $R[i+1…n]$ 分别变为记录个数增加1个的**新有序区**和记录个数减少1个的**新无序区**；
23 | - $n-1$ 趟结束，数组有序化了。
24 |
25 |
26 | 以数组A`{49,38,65,97,76,13,27,49}`为例，对n个元素的简单选择排序需要 `n-1` 趟处理。
27 |
28 | 
29 | 
30 | 
31 | 
32 |
33 | ## 3. 算法实现
34 | ```cpp
35 | void swap(int &a, int &b){
36 | int temp = a;
37 | a = b;
38 | b = temp;
39 | }
40 |
41 | void SelectSort(int array[], int n)
42 | {
43 | // 一共进行 n-1 趟, i 指代待排序的元素开头位置
44 | for (int i = 0; i < n - 1; i++){
45 | // 记录最小元素位置
46 | int min = i;
47 | // 在 array[i, n-1]中找最小的元素
48 | for (int j = i + 1; j < n; j++){
49 | // 更新最小的元素
50 | if (array[j] < array[min]){
51 | min = j;
52 | }
53 | }
54 |
55 | if (min != i){
56 | swap(array[i], array[min]);
57 | }
58 | }
59 | }
60 | ```
61 | ## 4. 算法性能
62 | ⽆论有序、逆序、还是乱序，⼀定需要 `n-1` 趟处理，总共需要对比关键字次数目：
63 | $(n-1) + (n-2)+ … + 1 = \frac{n(n-1)}{2}$
64 |
65 | 元素交换次数 < $n-1$
66 | - 时间复杂度 = $O(N^2)$
67 | - 空间复杂度 = $O(1)$
68 |
69 | 选择排序是不稳定的排序。
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/【DSA】数据结构与算法（C语言版本）/30 堆与堆排序.md:
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1 | #数据结构 #算法 #C
2 | # [89] 堆排序
3 | 堆排序也属于选择排序
4 | ## 1. 堆（heap）
5 | 若 $n$个 关键字序列 $L[1…n]$ 满⾜下⾯某⼀条性质，则称为堆（Heap）：
6 | 1. 若满⾜：$L(i)≥L(2i)$ ，且 $L(i)≥L(2i+1)$ $(1 ≤ i ≤n/2 )$ —— 大根堆（大顶堆，Max heap）
7 | 2. 若满⾜：$L(i)≤L(2i)$ ，且 $L(i)≤L(2i+1) (1 ≤ i ≤n/2)$ —— 小根堆（小顶堆， Min heap）
8 |
9 | 
10 |
11 | ## 2. 算法思想
12 | 思路：
13 | 把所有非终端结点都检查⼀遍，是否满足“大根堆”的要求，如果不满足，则进⾏调整⼤根堆，若元素互换破坏了下⼀级的堆，则采⽤相同的⽅法继续往下调整（小元素不断“下坠”）。
14 |
15 | 
16 |
17 | ## 3. 算法实现
18 | ```c
19 | // 建立大根堆
20 | void BuildMaxHeap(int array[], int len){
21 | // 从后往前调整所有非终端结点
22 | for (int i = len / 2; i > 0; i--){
23 | HeadAdjust(array, i, len);
24 | }
25 | }
26 |
27 | // 将以k为根的子树调整为大根堆
28 | void HeadAdjust(int array[], int k, int len){
29 | // array[0] 暂存子树的根结点
30 | array[0] = array[k];
31 | // 沿key较大的子结点向下筛选
32 | for (int i = 2 * k; i < len; i *= 2){
33 | // 取key较大的子结点的下标
34 | if (i < len && array[i] < array[i + 1]) {
35 | i++;
36 | }
37 | // 筛选结束
38 | if (array[0] >= array[i]) {
39 | break;
40 | }
41 | // 将array[i] 调整到双亲结点上
42 | // 修改k值, 以便继续向下筛选
43 | else {
44 | array[k] = array[i];
45 | k = i;
46 | }
47 | }
48 | array[k] = array[0];
49 | }
50 |
51 | // 堆排序
52 | void HeapSort(int array[], int len)
53 | {
54 | BuildMaxHeap(array, len);
55 | for (int i=len; i >1; i--) {
56 | swap(array[i], array[1]);
57 | HeadAdjust(array, 1, i - 1);
58 | }
59 | }
60 | ```
61 | ## 4. 算法性能
62 |
63 | # [90] 堆的插入删除
64 | 对于小根堆，新元素放到表尾，与父结点对比，若新元素比父结点更小，则将二者互换。新元素就这样一路"上升"，直到无法继续上升为止。
65 |
66 | 被删除的元素用堆底元素替代，然后让该元素不断"下坠"，直到无法下坠为止。
67 |
68 |
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/【DSA】数据结构与算法（C语言版本）/31 归并排序.md:
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1 | #数据结构 #算法 #C
2 | # [84] 归并排序(Merge Sort)
3 | ### 1. 算法思想
4 | 将多个已经有序的序列合并成一整个有序序列。
5 |
6 | ### 2. 算法过程
7 | 对比i，j所指元素，选择一个更小的放入到k所指的位置（使用双指针法）。
8 |
9 | 当只剩下一个子表未合并的时候，可以将该表剩下升序的其他元素全部加到总表之中。
10 | 核心操作：把数组当中内部的两个有序序列归并成一个。
11 |
12 | ### 3. 算法实现
13 | ```c
14 | // 辅助数组B
15 | int* B = (int *)malloc(n * sizeof(int));
16 |
17 | // A[low, mid] 和 A[mid+1, high] 各自有序，将两个部分归并
18 | void Merge (int A[], int low, int mid, int high){
19 | int i, j, k;
20 | for (k= low; k<=high; k++){
21 | B[k] = A[k];
22 | }
23 | // 将A中所有的元素复制到B中
24 | for (i = low, j = mid + 1, k = i; i <= mid && j <= high; k++){
25 | if (B[i] <= B[j]){
26 | A[k] = B[i++];
27 | } else {
28 | A[k] = B[j++];
29 | }
30 | }
31 | while (i <= mid){
32 | A[k++] = B[i++];
33 | }
34 | while (j <= high){
35 | A[k++] = B[i++];
36 | }
37 | }
38 |
39 | void MergeSort(int A[], int low, int high){
40 | if (low < high){
41 | int mid = (low + high) / 2;
42 | MergeSort(A, low, mid);
43 | MergeSort(A, mid + 1, high);
44 | MergeSort(A, low, mid, high);
45 | }
46 | }
47 | ```
48 |
49 |
50 |
51 |
52 |
53 |
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/【DSA】数据结构与算法（C语言版本）/32 基数排序.md:
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1 | #数据结构 #算法 #C
2 | # [85] 基数排序
3 | 基数排序，Radix Sort。
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/【DSA】数据结构与算法（C语言版本）/33 外部排序、败者树.md:
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1 | #数据结构 #算法 #C
2 | # [86] 外部排序
3 | 外存和内存之间是怎样进行数据交换的？
4 | 操作系统以“块”为单位对磁盘存储空间进行管理，如:每块大小1KB。各个磁盘块内存放着各种各样的数据。
5 | 使用归并排序的方式，最少只需要在内存中分配 3块 大小的缓冲区，即可对任意一个大文件进行排序。
6 |
7 |
8 | # [87] 败者树
9 |
10 | # [88] 置换选择排序
11 |
12 | # [89] 最佳归并树
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/【DSA】数据结构与算法（C语言版本）/34 常用算法 - 单调栈.md:
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1 | #算法
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/【DSA】数据结构与算法（C语言版本）/35 常用算法 - 单调栈.md:
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1 | #算法
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/【DSA】数据结构与算法（C语言版本）/36 常用算法 - 贪心.md:
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1 | #算法
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/【DSA】数据结构与算法（C语言版本）/37 常用算法 - 前缀和.md:
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1 | #算法
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/【DSA】数据结构与算法（C语言版本）/38 常用算法 - 分治.md:
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1 | #算法
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/【DSA】数据结构与算法（C语言版本）/40 常用算法 - 动态规划.md:
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1 | #算法
2 |
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/【DSA】数据结构与算法（C语言版本）/README.md:
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1 | #数据结构 #算法 #索引
2 |
3 | # DSA 目录索引
4 | # Ch01. 绪论与概要
5 | - [01 绪论与概要](01%20绪论与概要.md)
6 |
7 | # Ch02. 线性表
8 | - [02 顺序表](02%20顺序表.md)
9 | - [03 单链表](03%20单链表.md)
10 | - [04 双链表、循环链表与静态链表](04%20双链表、循环链表与静态链表.md)
11 | - [05 链表逆置](05%20链表逆置.md)
12 |
13 | # Ch03. 栈与队列
14 | - [06 栈与栈的应用](06%20栈与栈的应用.md)
15 | - [07 队列与队列的应用](07%20队列与队列的应用.md)
16 |
17 | # Ch04. 串
18 | - [08 串](08%20串.md)
19 | - [09 串的模式匹配 -- BF与KMP](09%20串的模式匹配%20--%20BF与KMP.md)
20 |
21 | # Ch05. 树
22 | - [10 树与二叉树](10%20树与二叉树.md)
23 | - [11 二叉树遍历](11%20二叉树遍历.md)
24 | - [12 二叉树线索化](12%20二叉树线索化.md)
25 | - [13 树和森林的遍历](13%20树和森林的遍历.md)
26 | - [14 哈夫曼编码、并查集](14%20哈夫曼编码、并查集.md)
27 | - [15 二叉排序树BST与平衡二叉树AVL](15%20二叉排序树BST与平衡二叉树AVL.md)
28 | - [16 红黑树](16%20红黑树.md)
29 | - [17 B树、B+树](17%20B树、B+树.md)
30 |
31 | # Ch06. 图
32 | - [18 图与图的存储方式](18%20图与图的存储方式.md)
33 | - [19 图的基本操作](19%20图的基本操作.md)
34 | - [20 图的最短路径问题](20%20图的最短路径问题.md)
35 | - [21 图的拓扑排序和关键路径](21%20图的拓扑排序和关键路径.md)
36 |
37 | # Ch07. 查找
38 | - [22 顺序查找、二分查找](22%20顺序查找、二分查找.md)
39 | - [23 分块查找、散列查找（哈希查找）](23%20分块查找、散列查找（哈希查找）.md)
40 | - [24 C语言的哈希实现 uthash库](24%20C语言的哈希实现%20uthash库.md)
41 |
42 | # Ch08. 排序
43 | - [25 排序算法概要、冒泡排序](25%20排序算法概要、冒泡排序.md)
44 | - [26 插入排序](26%20插入排序.md)
45 | - [27 希尔排序](27%20希尔排序.md)
46 | - [28 快速排序](28%20快速排序.md)
47 | - [29 选择排序](29%20选择排序.md)
48 | - [30 堆与堆排序](30%20堆与堆排序.md)
49 | - [31 归并排序](31%20归并排序.md)
50 | - [32 基数排序](32%20基数排序.md)
51 | - [33 外部排序、败者树](33%20外部排序、败者树.md)
52 |
53 | # Ch09.常用算法思想
54 | - [34 常用算法 - 单调栈](34%20常用算法%20-%20单调栈.md)
55 | - [36 常用算法 - 贪心](36%20常用算法%20-%20贪心.md)
56 | - [38 常用算法 - 分治](38%20常用算法%20-%20分治.md)
57 | - [39 常用算法 - 回溯法](39%20常用算法%20-%20回溯法.md)
58 | - [40 常用算法 - 动态规划](40%20常用算法%20-%20动态规划.md)
59 | - [37 常用算法 - 前缀和](37%20常用算法%20-%20前缀和.md)
60 | - [35 常用算法 - 单调栈](35%20常用算法%20-%20单调栈.md)
61 |
62 |
63 |
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/【DSA】数据结构与算法（C语言版本）/src/graph/BFS.c:
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1 | #include <stdio.h>
2 | #include <stdbool.h>
3 |
4 | #include "adjacency_matrix.h"
5 | #ifdef ADJACENCY_MATRIX_H
6 | typedef MGraph Graph;
7 | typedef struct Queue
8 | {
9 | int data[100];
10 | int rear, front;
11 | } Queue;
12 |
13 | void visit(int v)
14 | {
15 | /* ....code... */
16 | }
17 |
18 | void Init(Queue q) {
19 | /* ....code... */
20 | }
21 |
22 | void EnQueue(Queue q, int val) {
23 | /* ....code... */
24 | }
25 |
26 | void DeQueue(Queue q, int val) {
27 | /* ....code... */
28 | }
29 |
30 | bool IsEmptyQue(Queue q) {
31 | /* ....code... */
32 | }
33 |
34 | // 图G中顶点x的第⼀个邻接点
35 | int FirstNeighbor(Graph G, int v){
36 | /* ....code... */
37 | }
38 |
39 | // 返回除自身之外顶点w的下⼀个邻接点的顶点号
40 | int NextNeighbor(Graph G, int v, int w){
41 | /* ....code... */
42 | }
43 |
44 | Queue Q;
45 | int w;
46 |
47 | /**************** 实现BFS *******************/
48 |
49 | bool visited[MaxVertexNum]; // 访问标记数组
50 |
51 | // 对图G进行广度优先遍历
52 | void BFSTraverse(Graph G)
53 | {
54 | // 初始化标记数组
55 | for (int i = 0; i < G.vexNum; i++) {
56 | visited[i] = false;
57 | }
58 |
59 | Init(Q);
60 | // 从起始点开始遍历
61 | for (int i = 0; i < G.vexNum; i++)
62 | {
63 | if (!visited[i]) { // 对每一个连通分量调用一次BFS
64 | BFS(G, i); // 防止出现隔离的顶点
65 | }
66 | }
67 | }
68 |
69 | // 广度优先遍历
70 | void BFS(Graph G, int v)
71 | {
72 | visit(v); // 从顶点出发开始遍历
73 | visited[v] = true; // v已经被访问到
74 | EnQueue(Q, v); // 将v压入队列Q
75 | while (!IsEmptyQue(Q)) {
76 | DeQueue(Q, v); // v出队列Q
77 |
78 | // 检测v的所有邻接顶点
79 | for (w = FirstNeighbor(G, v) ;w >= 0; w = NextNeighbor(G, v, w))
80 | {
81 | if (!visited[w]) // w为未曾访问的顶点
82 | {
83 | visit(w); // 访问
84 | visited[w] = true;
85 | EnQueue(Q, w); // 再将w顶点压入队列中
86 | }
87 | }
88 | }
89 | }
90 |
91 | #endif
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/【DSA】数据结构与算法（C语言版本）/src/graph/DFS.c:
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1 | #include <stdio.h>
2 | #include <stdbool.h>
3 |
4 | #include "adjacency_matrix.h"
5 | #ifdef ADJACENCY_MATRIX_H
6 | typedef MGraph Graph;
7 |
8 | void visit(int v)
9 | {
10 | /* ....code... */
11 | }
12 |
13 | // 图G中顶点x的第⼀个邻接点
14 | int FirstNeighbor(Graph G, int v){
15 | /* ....code... */
16 | }
17 |
18 | // 返回除自身之外顶点w的下⼀个邻接点的顶点号
19 | int NextNeighbor(Graph G, int v, int w){
20 | /* ....code... */
21 | }
22 |
23 | int w;
24 |
25 | /**************** 实现DFS *******************/
26 | bool visited[MaxVertexNum]; // 访问标记数组
27 |
28 | // 对图G进行深度优先遍历
29 | void DFSTraverse(Graph G)
30 | {
31 | // 初始化标记数组
32 | for (int i = 0; i < G.vexNum; i++) {
33 | visited[i] = false;
34 | }
35 | // 从起始点开始遍历
36 | for (int i = 0; i < G.vexNum; i++)
37 | {
38 | if (!visited[i]) { // 对每一个连通分量调用一次DFS
39 | DFS(G, i); // 防止出现隔离的顶点
40 | }
41 | }
42 | }
43 |
44 | void DFS(Graph G, int v)
45 | {
46 | visit(v); // 访问顶点v
47 | visited[v] = true; // 更新标记数组
48 |
49 | // 检测v的下一个邻接顶点
50 | for (w = FirstNeighbor(G, v) ;w >= 0; w = NextNeighbor(G, v, w))
51 | {
52 | if (!visited[w])
53 | {
54 | DFS(G,w);
55 | }
56 | }
57 | }
58 |
59 |
60 |
61 | #endif
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/graph/adjacency_list.h:
--------------------------------------------------------------------------------
1 | #ifndef ADJACENCY_LIST_H
2 | #define ADJACENCY_LIST_H
3 |
4 | #include <stdio.h>
5 | #include <limits.h>
6 |
7 | #define MaxVertexNum 100 // 顶点数目最大值
8 | typedef char VertexType; // 顶点数据类型，可以按照需要重定义
9 |
10 | // 边，弧
11 | typedef struct ArcNode
12 | {
13 | int adjVex; // 边、弧指向哪个结点
14 | ArcNode *next; // 指向下一条弧的指针
15 | // InfoType info; // 边权值
16 | } ArcNode;
17 |
18 | // 顶点
19 | typedef struct VNode {
20 | VertexType data; // 顶点信息
21 | ArcNode *first; // 第一条边/弧
22 | } VNode, AdjList[MaxVertexNum];
23 |
24 | // 用邻接表存储的图
25 | typedef struct adjacency_list
26 | {
27 | AdjList vertices;
28 | int vexNum, arcNum;
29 | } ALGraph; // Adjacency List Graph
30 |
31 | #endif // ADJACENCY_LIST_H
32 |
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/graph/adjacency_matrix.h:
--------------------------------------------------------------------------------
1 | #ifndef ADJACENCY_MATRIX_H
2 | #define ADJACENCY_MATRIX_H
3 |
4 | #include <stdio.h>
5 | #include <limits.h>
6 |
7 | #define MaxVertexNum 100 // 顶点数目最大值
8 |
9 | // 邻接矩阵定义
10 | typedef struct
11 | { // 顶点表，数据类型可变，可以存放更复杂信息
12 | char vex[MaxVertexNum];
13 | // 邻接矩阵，边表，可以使用bool类型或者枚举类型
14 | int edge[MaxVertexNum][MaxVertexNum];
15 | // 图当前的顶点数和边数/弧数
16 | int vexNum, arcNum;
17 | } MGraph;
18 |
19 |
20 | #define INFINITY INT_MAX // 表示无穷
21 |
22 | typedef char VertexType; // 顶点数据类型，可以按照需要重定义
23 | typedef int EdgeType; // 带权图上边上权值数据类型，可以按照需要重定义
24 | typedef struct
25 | {
26 | // 顶点
27 | VertexType vex[MaxVertexNum];
28 | // 边的权
29 | EdgeType EdgeType[MaxVertexNum][MaxVertexNum];
30 | // 图当前的顶点数和边数/弧数
31 | int vexNum, arcNum;
32 | } MGraph_Weight;
33 |
34 | #endif // ADJACENCY_MATRIX_H
35 |
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/graph/adjacency_multi_list.h:
--------------------------------------------------------------------------------
1 | #ifndef ADJACENCY_MULTI_LIST_H
2 | #define ADJACENCY_MULTI_LIST_H
3 |
4 | #include <stdio.h>
5 | #include <limits.h>
6 |
7 | #define MaxVertexNum 100 // 图中顶点的最大数量
8 |
9 | typedef char VertexType; // 图中顶点的数据类型
10 | typedef float InfoType; // 表示弧额外信息的数据类型
11 |
12 | // 边标志域
13 | typedef enum {
14 | unvisited = 0,
15 | visited
16 | } VisitIf;
17 |
18 | // 表示链表中的各个结点
19 | typedef struct EBox {
20 | VisitIf mark; // 标志域
21 | int ivex, jvex; // 边两边顶点在顺序表中的位置下标
22 | struct EBox* ilink, * jlink; // 分别指向与ivex、jvex相关的下一个边结点
23 | InfoType* info; // 边的其它信息
24 | } EBox;
25 |
26 | // 存储图中的各个顶点
27 | typedef struct VexBox {
28 | VertexType data; // 顶点数据域
29 | EBox* firstedge; // 指向当前顶点对应的链表
30 | } VexBox;
31 |
32 | // 表示邻接多重表结构
33 | typedef struct {
34 | VexBox adjmulist[MaxVertexNum]; // 存储图中顶点的顺序表
35 | int vexnum, edgenum; // 记录图中的顶点数量和边数量
36 | } AMLGraph;
37 |
38 | #endif // ADJACENCY_MULTI_LIST_H
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/graph/orthogonal_linked_list.h:
--------------------------------------------------------------------------------
1 | #ifndef ORTHOGONAL_LINKED_LIST
2 | #define ORTHOGONAL_LINKED_LIST
3 |
4 | #include <stdio.h>
5 | #include <limits.h>
6 |
7 | #define MaxVertexNum 100 // 图中顶点的最大数量
8 |
9 | typedef char VertexType; // 图中顶点的数据类型
10 | typedef float InfoType; // 表示弧额外信息的数据类型
11 |
12 | // 表示链表中存储弧的结点
13 | typedef struct ArcBox {
14 | int tailvex, headvex; // 弧尾、弧头对应顶点在顺序表中的位置下标
15 | struct ArcBox* hlik, * tlink; // hlik 指向下一个以当前顶点为弧头的弧结点；
16 | // tlink 指向下一个以当前顶点为弧尾的弧结点；
17 | // InfoType info; // 存储弧相关信息的指针,有向边的权
18 | } ArcBox;
19 |
20 | // 表示顺序表中的各个顶点
21 | typedef struct VexNode {
22 | VertexType data; // 顶点的数据域
23 | ArcBox* firstin, * firstout; // 指向以该顶点为弧头和弧尾的链表首个结点
24 | } VexNode;
25 |
26 | // 表示十字链表存储结构
27 | typedef struct {
28 | VexNode xlist[MaxVertexNum]; // 存储顶点的顺序表
29 | int vexnum, arcnum; // 记录图的顶点数和弧数
30 | } OLGraph;
31 |
32 | #endif // ORTHOGONAL_LINKED_LIST
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/search/binary_search.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <string.h>
3 |
4 |
5 | int BinarySearch(int *L, int len, int target)
6 | {
7 | int low = 0, high = len - 1, mid;
8 | while (low <= high) {
9 | mid = (low + high) / 2; // 对序数取半
10 | if (L[mid] == target){
11 | return mid; // 查找成功直接返回序数
12 | }
13 | else if (L[mid] > target){
14 | high = mid - 1; // 开始从前半部分查找
15 | }
16 | else {
17 | low = mid + 1; // 开始从后半部分查找
18 | }
19 | }
20 | return -1; // 查找失败，返回-1值
21 | }
22 |
23 | int main()
24 | {
25 | int L[] = {7, 10, 13, 16, 19, 29, 32, 33, 37, 41, 43};
26 | int target = 33;
27 | int index = BinarySearch(L, sizeof(L) / sizeof(L[0]), target);
28 |
29 | /* 预期输出： 7
30 | index 0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 - 9 - 10
31 | data 7, 10, 13, 16, 19, 29, 32, 33, 37, 41, 43
32 | */
33 | printf("index of target[%d] = %d\n", target, index);
34 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/sort/bubble_sort.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <stdbool.h>
3 |
4 | #define ARR_LEN 255 /* 数组长度上限 */
5 | #define elemType int /* 元素类型 */
6 |
7 | /* 冒泡排序
8 | 1. 从当前元素起，向后依次比较每一对相邻元素，若逆序则互换
9 | 2. 对所有元素均重复以上步骤，直至最后一个元素
10 | elemType arr[]: 排序目标数组;
11 | int len: 元素个数
12 | */
13 | void BubbleSort(int arr[], int len)
14 | {
15 |
16 | int i, j, temp;
17 | _Bool exchanged = true;
18 |
19 | /* 外循环为排序趟数，len个数进行len-1趟,
20 | 只有交换过, exchanged值为true才有必要执行循环,
21 | 否则exchanged值为false不执行循环 */
22 | for (i = 0; exchanged && i < len - 1; i++)
23 | {
24 | exchanged = false;
25 | /* 内循环为每趟比较的次数，
26 | 第i趟比较 len-i 次 */
27 | for (j = 0; j < len - 1 - i; j++)
28 | {
29 | /* 相邻元素比较，若逆序则互换（升序为左大于右，逆序反之） */
30 | if (arr[j] > arr[j + 1])
31 | {
32 | temp = arr[j];
33 | arr[j] = arr[j + 1];
34 | arr[j + 1] = temp;
35 | exchanged = true; /* 只有数值互换过, exchanged才会从false变成true,
36 | 否则数列已经排序完成, exchanged值仍然为false, 没必要排序 */
37 | }
38 | }
39 | }
40 | }
41 |
42 | int main(void)
43 | {
44 | int arr[ARR_LEN] = {3, 5, 1, -7, 4, 9, -6, 8, 10, 4};
45 | int len = 10;
46 | int i;
47 |
48 | BubbleSort(arr, len);
49 | for (i = 0; i < len; i++)
50 | {
51 | printf("%d\t", arr[i]);
52 | }
53 | putchar('\n');
54 |
55 | return 0;
56 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/sort/heap_sort.c:
--------------------------------------------------------------------------------
1 | // Heap Sort in C
2 | #include <stdio.h>
3 |
4 | // Function to swap the position of two elements
5 | void swap(int* a, int* b)
6 | {
7 |
8 | int temp = *a;
9 | *a = *b;
10 | *b = temp;
11 | }
12 |
13 | // To heapify a subtree rooted with node i
14 | // which is an index in arr[].
15 | // n is size of heap
16 | void heapify(int arr[], int N, int i)
17 | {
18 | // Find largest among root,
19 | // left child and right child
20 |
21 | // Initialize largest as root
22 | int largest = i;
23 |
24 | // left = 2*i + 1
25 | int left = 2 * i + 1;
26 |
27 | // right = 2*i + 2
28 | int right = 2 * i + 2;
29 |
30 | // If left child is larger than root
31 | if (left < N && arr[left] > arr[largest])
32 |
33 | largest = left;
34 |
35 | // If right child is larger than largest
36 | // so far
37 | if (right < N && arr[right] > arr[largest])
38 |
39 | largest = right;
40 |
41 | // Swap and continue heapifying
42 | // if root is not largest
43 | // If largest is not root
44 | if (largest != i) {
45 |
46 | swap(&arr[i], &arr[largest]);
47 |
48 | // Recursively heapify the affected
49 | // sub-tree
50 | heapify(arr, N, largest);
51 | }
52 | }
53 |
54 | // Main function to do heap sort
55 | void heapSort(int arr[], int N)
56 | {
57 |
58 | // Build max heap
59 | for (int i = N / 2 - 1; i >= 0; i--)
60 |
61 | heapify(arr, N, i);
62 |
63 | // Heap sort
64 | for (int i = N - 1; i >= 0; i--) {
65 |
66 | swap(&arr[0], &arr[i]);
67 |
68 | // Heapify root element
69 | // to get highest element at
70 | // root again
71 | heapify(arr, i, 0);
72 | }
73 | }
74 |
75 | // A utility function to print array of size n
76 | void printArray(int arr[], int N)
77 | {
78 | for (int i = 0; i < N; i++)
79 | printf("%d ", arr[i]);
80 | printf("\n");
81 | }
82 |
83 | // Driver's code
84 | int main()
85 | {
86 | int arr[] = { 12, 11, 13, 5, 6, 7 };
87 | int N = sizeof(arr) / sizeof(arr[0]);
88 |
89 | // Function call
90 | heapSort(arr, N);
91 | printf("Sorted array is\n");
92 | printArray(arr, N);
93 | }
94 |
95 | // This code is contributed by _i_plus_plus_.
96 |
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/sort/insert_sort.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 |
3 | int Insert_sort(int s[], int n) /* 自定义函数 Insert_sort()*/
4 | {
5 | int i, j;
6 | for (i = 2; i <= n; i++) // 数组下标从2开始，s[0]做监视哨，s[1]一个数据无可比性
7 | {
8 | s[0] = s[i]; // 给监视哨赋值
9 | j = i - 1; // 确定要比较元素的最右边位
10 |
11 | while (s[0] < s[j])
12 | {
13 | s[j + 1] = s[j]; // 数据右移
14 | j--; // 产移向左边一个未比较的数
15 | }
16 |
17 | s[j + 1] = s[0]; // 在确定的位置插入s[i]
18 | }
19 | return 0;
20 | }
21 |
22 | int main()
23 | {
24 | int a[11], i; // 定义数组及变量为基木整甩
25 | printf("input 10 nums:\n");
26 | for (i = 1; i <= 10; i++)
27 | {
28 | scanf("%d", &a[i]); // 接收从键盘输入的10个数据到数组a中
29 | }
30 |
31 | printf("original order\n");
32 |
33 | for (i = 1; i < 11; i++) {
34 | printf("%5d", a[i]); // 将未排序前的顺序输出
35 | }
36 |
37 | Insert_sort(a, 10); // 调用自定义函数 Insert_sort()
38 | printf("\n after sort:\n");
39 |
40 | for (i = 1; i < 11; i++) {
41 | printf("%5d", a[i]); // 将排序后的数组输出
42 | }
43 | printf("\n");
44 | return 0;
45 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/sort/quick_sort.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 |
3 | int Partition(int array[], int low, int high)
4 | {
5 | // 把第一个元素当作枢轴
6 | int pivot = array[low];
7 |
8 | // 用low、high搜索枢轴的最终位置，
9 | // 当low 与 high 相碰的时候和或者 low 溢出 high 的时候结束
10 | while (low < high)
11 | {
12 | // 比枢轴小的元素移动到左端
13 | while (low < high && array[high] >= pivot)
14 | {
15 | high--;
16 | }
17 | array[low] = array[high];
18 |
19 | // 比枢轴大的元素移动到右端
20 | while (low < high && array[low] <= pivot)
21 | {
22 | low++;
23 | }
24 | array[high] = array[low];
25 | }
26 | array[low] = pivot;
27 | return low;
28 | }
29 |
30 | // 快速排序
31 | void QuickSort(int array[], int low, int high)
32 | {
33 | if (low < high)
34 | {
35 | int pivot = Partition(array, low, high);
36 | QuickSort(array, low, pivot - 1);
37 | QuickSort(array, pivot + 1, high);
38 | }
39 | }
40 |
41 | /**************************************************
42 | *函数名：display
43 | *作用：打印数组元素
44 | *参数：array - 打印的数组，maxlen - 数组元素个数
45 | *返回值：无
46 | **************************************************/
47 | void display(int array[], int maxlen)
48 | {
49 | int i;
50 |
51 | for (i = 0; i < maxlen; i++)
52 | {
53 | printf("%-3d", array[i]);
54 | }
55 | printf("\n");
56 |
57 | return;
58 | }
59 |
60 |
61 | int main()
62 | {
63 | int array[] = {49, 38, 65, 97, 76, 13, 27, 49};
64 | int low = 0, high = 7;
65 |
66 | QuickSort(array, low, high);
67 | display(array, sizeof(array) / sizeof(array[0]));
68 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/sort/shell_sort.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <stdlib.h>
3 | #include <string.h>
4 |
5 | #ifndef N
6 | #define N 100
7 | #endif
8 | int arr[N];
9 |
10 | int Shell_Sort(int *arr)
11 | {
12 | register int i, j, k, tmp;
13 | int incre; // 选择一个增量，这里我们用简单的二分法
14 |
15 | for (incre = N / 20; incre > 0; incre /= 2)
16 | {
17 | for (i = incre; i < N / 10; i++)
18 | {
19 | tmp = arr[i];
20 | // 很明显和插排的不同就是插排这里是j = i - 1
21 | j = i - incre;
22 | while (j >= 0 && tmp < arr[j])
23 | {
24 | arr[j + incre] = arr[j];
25 | j -= incre;
26 | }
27 | arr[j + incre] = tmp;
28 | }
29 | }
30 | }
31 |
32 | int main(int argc, int *argv[])
33 | {
34 | int i;
35 | printf("please enter 10 numbers: \n");
36 |
37 | for (i = 0; i < N / 10; i++)
38 | {
39 | scanf("%d", &arr[i]);
40 | }
41 | Shell_Sort(arr);
42 |
43 | printf("\n");
44 | printf("the ordered array is: \n");
45 | for (i = 0; i < N / 10; i++)
46 | {
47 | printf("%4d", arr[i]);
48 | }
49 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/string/pattern_matching_bf.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <string.h>
3 |
4 |
5 | int Index_BF(char *main, int mainLen, char *pattern, int patLen)
6 | {
7 | int pStr = 0, pPat = 0;
8 | int matchCnt = 0;
9 |
10 | // 必须满足指针小于字符串长度，否则比较无意义。
11 | while (pStr < mainLen && pPat < patLen) {
12 | // 如果有字符相等，继续比较后续字符串
13 | if (main[pStr] == pattern[pPat]) {
14 | ++pStr;
15 | ++pPat;
16 | } else {
17 | /* step = pPat - 0 = pPat = pStr - PStrOrigin,
18 | pStrOrigin = pStr - pPat
19 | pStrNext = pStr - pPat + 1
20 | */
21 | pStr = pStr - pPat + 1;
22 | pPat = 0; // 失败从0位置开始
23 | }
24 | matchCnt++;
25 | }
26 |
27 | printf("matching counts = %d\n", matchCnt); // 16次
28 |
29 | // 匹配时，满足等于strlen
30 | if (pPat >= patLen) {
31 | return pStr - patLen;
32 | } else {
33 | return 0;
34 | }
35 | }
36 |
37 | int main()
38 | {
39 | char mainStr[] = "ababababca";
40 | char patternStr[] = "abababca";
41 |
42 | printf("str length of main Str [%s] = %d\n",mainStr, strlen(mainStr));
43 | printf("str length of patten Str [%s] = %d\n",patternStr, strlen(patternStr));
44 |
45 | int index = Index_BF(mainStr,strlen(mainStr), patternStr,strlen(patternStr));
46 |
47 | /* 预期匹配位置：2
48 | index 0 1 2 3 4 5 6 7 8 9
49 | main a - b - a - b - a - b - a - b - c - a
50 | pattern a - b - a - b - a - b - c - a */
51 | printf("Locate pattern matching :index [%d].\n", index);
52 | }
53 |
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/string/pattern_matching_kmp.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <string.h>
3 |
4 | int next[8] = {0};
5 |
6 | void GetNext(char *pattern, int *next)
7 | {
8 | next[0] = -1;
9 | int i = 0, j = -1;
10 |
11 | while (i < (int)strlen(pattern))
12 | {
13 | if (j == -1 || pattern[i] == pattern[j])
14 | {
15 | ++i;
16 | ++j;
17 | next[i] = j;
18 | }
19 | else
20 | j = next[j];
21 | }
22 | }
23 |
24 | int Index_KMP(char *main, int mainLen, char *pattern, int patLen)
25 | {
26 | int pStr = 0, pPat = 0;
27 | int matchCnt = 0;
28 |
29 | // 必须满足指针小于字符串长度，否则比较无意义。
30 | while (pStr < mainLen && pPat < patLen) {
31 | // 如果有字符相等，继续比较后续字符串
32 | if (pPat == -1 ||main[pStr] == pattern[pPat]) {
33 | ++pStr;
34 | ++pPat;
35 | } else {
36 | pPat = next[pPat];
37 | }
38 | matchCnt++;
39 | }
40 |
41 | printf("matching counts = %d\n", matchCnt); // 11次
42 |
43 | // 匹配时，满足等于strlen
44 | if (pPat >= patLen) {
45 | return pStr - patLen;
46 | } else {
47 | return 0;
48 | }
49 | }
50 |
51 |
52 | int main()
53 | {
54 | char mainStr[] = "ababababca";
55 | char patternStr[] = "abababca";
56 |
57 | printf("str length of main Str [%s] = %d\n",mainStr, strlen(mainStr));
58 | printf("str length of patten Str [%s] = %d\n",patternStr, strlen(patternStr));
59 | GetNext(patternStr, next);
60 | for (size_t i = 0; i < 8; i++)
61 | {
62 | printf("next[%d] = %d\n", i, next[i]);
63 | }
64 |
65 | int index = Index_KMP(mainStr,strlen(mainStr), patternStr,strlen(patternStr));
66 |
67 | /* 预期匹配位置：2
68 | index 0 1 2 3 4 5 6 7 8 9
69 | main a - b - a - b - a - b - a - b - c - a
70 | pattern a - b - a - b - a - b - c - a */
71 | printf("Locate pattern matching :index [%d].\n", index);
72 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/tree/tree_in_order.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <stdlib.h>
3 | #include <string.h>
4 |
5 | #define ARRAY_MAX_SIZE 100
6 | typedef struct BiTNode {
7 | int data;
8 | struct BiTNode *lchild, *rchild;
9 | } BiTNode, *BiTree;
10 |
11 | // pos作为指针传参，是需要将其值带出来
12 | void PushBack(int* array, int* pos, int data)
13 | {
14 | if (*pos >= ARRAY_MAX_SIZE) {
15 | return;
16 | }
17 | array[*pos] = data;
18 | (*pos)++;
19 | }
20 |
21 | // 测试输出Array
22 | void OutPutArray(int* array, int len)
23 | {
24 | for(int i = 0; i < len; i++)
25 | {
26 | printf("array[%d] = %d\n", i, array[i]);
27 | }
28 | return;
29 | }
30 |
31 | void InOrderTraverse(BiTree binaryTree, int* array, int* pos)
32 | {
33 | if (binaryTree == NULL) {
34 | return;
35 | }
36 |
37 | InOrderTraverse(binaryTree->lchild, array, pos);
38 | PushBack(array, pos, binaryTree->data);
39 | InOrderTraverse(binaryTree->rchild, array, pos);
40 |
41 | return;
42 | }
43 |
44 | void BiTreeInsertToArray(BiTree binaryTree, int* array)
45 | {
46 | int pos = 0;
47 | InOrderTraverse(binaryTree, array, &pos);
48 | OutPutArray(array, pos);
49 |
50 | return;
51 | }
52 |
53 | /**********************
54 | 测试代码框架
55 | 二叉树结构：
56 | 1
57 | / \
58 | 2 3
59 | / \ /
60 | 4 5 6
61 | /
62 | 7
63 | **********************/
64 |
65 | // 程序执行即结束，free
66 | BiTree CreateBiTree()
67 | {
68 | // 1
69 | BiTree tree = NULL;
70 | tree = (BiTNode*)malloc(sizeof(BiTNode));
71 | tree->data = 1;
72 |
73 | // 2、3
74 | BiTree tree_2 = (BiTNode*)malloc(sizeof(BiTNode));
75 | tree_2->data = 2;
76 | BiTree tree_3 = (BiTNode*)malloc(sizeof(BiTNode));
77 | tree_3->data = 3;
78 | tree->lchild = tree_2, tree->rchild = tree_3;
79 | tree_3->rchild = NULL;
80 |
81 | // 4、5
82 | BiTree tree_4 = (BiTNode*)malloc(sizeof(BiTNode));
83 | tree_4->data = 4;
84 | BiTree tree_5 = (BiTNode*)malloc(sizeof(BiTNode));
85 | tree_5->data = 5;
86 | tree_2->lchild = tree_4, tree_2->rchild = tree_5;
87 |
88 | tree_4->rchild = NULL;
89 | tree_5->lchild = NULL, tree_5->rchild = NULL;
90 |
91 | // 6
92 | BiTree tree_6 = (BiTNode*)malloc(sizeof(BiTNode));
93 | tree_6->data = 6;
94 | tree_3->lchild = tree_6;
95 |
96 | tree_6->lchild = NULL, tree_6->rchild = NULL;
97 |
98 | // 7
99 | BiTree tree_7 = (BiTNode*)malloc(sizeof(BiTNode));
100 | tree_7->data = 7;
101 | tree_4->lchild = tree_7;
102 | tree_7->lchild = NULL, tree_7->rchild = NULL;
103 |
104 | return tree;
105 | }
106 |
107 | int main()
108 | {
109 | BiTree tree = CreateBiTree();
110 | int array[ARRAY_MAX_SIZE];
111 |
112 | // 预期输出： 7 4 2 5 1 6 3 ---> 中序遍历
113 | BiTreeInsertToArray(tree, array);
114 |
115 | return 0;
116 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/tree/tree_level_order.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <stdlib.h>
3 | #include <string.h>
4 |
5 | typedef struct BiTNode
6 | {
7 | int data; // 数据域
8 | struct BiTNode *lchild, *rchild; // 左右孩子指针
9 | } BiTNode, *BiTree;
10 |
11 | // 初始化队头和队尾指针开始时都为0
12 | int front = 0, rear = 0;
13 |
14 |
15 |
16 | // 入队函数
17 | void EnQueue(BiTree *a, BiTree node)
18 | {
19 | a[rear++] = node;
20 | }
21 |
22 | // 出队函数
23 | BiTNode *DeQueue(BiTree *a)
24 | {
25 | return a[front++];
26 | }
27 |
28 | // 输出函数
29 | void OutputNode(BiTree node)
30 | {
31 | printf("%d ", node->data);
32 | }
33 |
34 | /**********************
35 | 测试代码框架
36 | 二叉树结构：
37 | 1
38 | / \
39 | 2 3
40 | / \ /
41 | 4 5 6
42 | /
43 | 7
44 | **********************/
45 |
46 | // 程序执行即结束，free
47 | BiTree CreateBiTree()
48 | {
49 | // 1
50 | BiTree tree = NULL;
51 | tree = (BiTNode*)malloc(sizeof(BiTNode));
52 | tree->data = 1;
53 |
54 | // 2、3
55 | BiTree tree_2 = (BiTNode*)malloc(sizeof(BiTNode));
56 | tree_2->data = 2;
57 | BiTree tree_3 = (BiTNode*)malloc(sizeof(BiTNode));
58 | tree_3->data = 3;
59 | tree->lchild = tree_2, tree->rchild = tree_3;
60 | tree_3->rchild = NULL;
61 |
62 | // 4、5
63 | BiTree tree_4 = (BiTNode*)malloc(sizeof(BiTNode));
64 | tree_4->data = 4;
65 | BiTree tree_5 = (BiTNode*)malloc(sizeof(BiTNode));
66 | tree_5->data = 5;
67 | tree_2->lchild = tree_4, tree_2->rchild = tree_5;
68 |
69 | tree_4->rchild = NULL;
70 | tree_5->lchild = NULL, tree_5->rchild = NULL;
71 |
72 | // 6
73 | BiTree tree_6 = (BiTNode*)malloc(sizeof(BiTNode));
74 | tree_6->data = 6;
75 | tree_3->lchild = tree_6;
76 |
77 | tree_6->lchild = NULL, tree_6->rchild = NULL;
78 |
79 | // 7
80 | BiTree tree_7 = (BiTNode*)malloc(sizeof(BiTNode));
81 | tree_7->data = 7;
82 | tree_4->lchild = tree_7;
83 | tree_7->lchild = NULL, tree_7->rchild = NULL;
84 |
85 | return tree;
86 | }
87 |
88 | // 预期输出： 1 2 3 4 5 6 7 ---> 层序遍历
89 | int main()
90 | {
91 | BiTree tree = CreateBiTree();
92 |
93 | BiTNode *p;
94 | BiTree a[20]; // 采用顺序队列，初始化创建队列数组
95 | EnQueue(a, tree); // 根结点入队
96 | while (front < rear) // 当队头和队尾相等时，表示队列为空
97 | {
98 | p = DeQueue(a); // 队头结点出队
99 | OutputNode(p); // 将队头结点的左右孩子依次入队
100 |
101 | if (p->lchild != NULL)
102 | {
103 | EnQueue(a, p->lchild);
104 | }
105 | if (p->rchild != NULL)
106 | {
107 | EnQueue(a, p->rchild);
108 | }
109 | }
110 | return 0;
111 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/tree/tree_post_order.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <stdlib.h>
3 | #include <string.h>
4 |
5 | #define ARRAY_MAX_SIZE 100
6 | typedef struct BiTNode {
7 | int data;
8 | struct BiTNode *lchild, *rchild;
9 | } BiTNode, *BiTree;
10 |
11 | // pos作为指针传参，是需要将其值带出来
12 | void PushBack(int* array, int* pos, int data)
13 | {
14 | if (*pos >= ARRAY_MAX_SIZE) {
15 | return;
16 | }
17 | array[*pos] = data;
18 | (*pos)++;
19 | }
20 |
21 | // 测试输出Array
22 | void OutPutArray(int* array, int len)
23 | {
24 | for(int i = 0; i < len; i++)
25 | {
26 | printf("array[%d] = %d\n", i, array[i]);
27 | }
28 | return;
29 | }
30 |
31 | void PostOrderTraverse(BiTree binaryTree, int* array, int* pos)
32 | {
33 | if (binaryTree == NULL) {
34 | return;
35 | }
36 |
37 | PostOrderTraverse(binaryTree->lchild, array, pos);
38 | PostOrderTraverse(binaryTree->rchild, array, pos);
39 | PushBack(array, pos, binaryTree->data);
40 | return;
41 | }
42 |
43 | void BiTreeInsertToArray(BiTree binaryTree, int* array)
44 | {
45 | int pos = 0;
46 | PostOrderTraverse(binaryTree, array, &pos);
47 | OutPutArray(array, pos);
48 |
49 | return;
50 | }
51 |
52 | /**********************
53 | 测试代码框架
54 | 二叉树结构：
55 | 1
56 | / \
57 | 2 3
58 | / \ /
59 | 4 5 6
60 | /
61 | 7
62 | **********************/
63 |
64 | // 程序执行即结束，free
65 | BiTree CreateBiTree()
66 | {
67 | // 1
68 | BiTree tree = NULL;
69 | tree = (BiTNode*)malloc(sizeof(BiTNode));
70 | tree->data = 1;
71 |
72 | // 2、3
73 | BiTree tree_2 = (BiTNode*)malloc(sizeof(BiTNode));
74 | tree_2->data = 2;
75 | BiTree tree_3 = (BiTNode*)malloc(sizeof(BiTNode));
76 | tree_3->data = 3;
77 | tree->lchild = tree_2, tree->rchild = tree_3;
78 | tree_3->rchild = NULL;
79 |
80 | // 4、5
81 | BiTree tree_4 = (BiTNode*)malloc(sizeof(BiTNode));
82 | tree_4->data = 4;
83 | BiTree tree_5 = (BiTNode*)malloc(sizeof(BiTNode));
84 | tree_5->data = 5;
85 | tree_2->lchild = tree_4, tree_2->rchild = tree_5;
86 |
87 | tree_4->rchild = NULL;
88 | tree_5->lchild = NULL, tree_5->rchild = NULL;
89 |
90 | // 6
91 | BiTree tree_6 = (BiTNode*)malloc(sizeof(BiTNode));
92 | tree_6->data = 6;
93 | tree_3->lchild = tree_6;
94 |
95 | tree_6->lchild = NULL, tree_6->rchild = NULL;
96 |
97 | // 7
98 | BiTree tree_7 = (BiTNode*)malloc(sizeof(BiTNode));
99 | tree_7->data = 7;
100 | tree_4->lchild = tree_7;
101 | tree_7->lchild = NULL, tree_7->rchild = NULL;
102 |
103 | return tree;
104 | }
105 |
106 | int main()
107 | {
108 | BiTree tree = CreateBiTree();
109 | int array[ARRAY_MAX_SIZE];
110 |
111 | // 预期输出： 7 4 5 2 6 3 1 ---> 后序遍历
112 | BiTreeInsertToArray(tree, array);
113 |
114 | return 0;
115 | }
--------------------------------------------------------------------------------
/【DSA】数据结构与算法（C语言版本）/src/tree/tree_pre_order.c:
--------------------------------------------------------------------------------
1 | #include <stdio.h>
2 | #include <stdlib.h>
3 | #include <string.h>
4 |
5 | #define ARRAY_MAX_SIZE 100
6 | typedef struct BiTNode {
7 | int data;
8 | struct BiTNode *lchild, *rchild;
9 | } BiTNode, *BiTree;
10 |
11 | // pos作为指针传参，是需要将其值带出来
12 | void PushBack(int* array, int* pos, int data)
13 | {
14 | if (*pos >= ARRAY_MAX_SIZE) {
15 | return;
16 | }
17 | array[*pos] = data;
18 | (*pos)++;
19 | }
20 |
21 | // 测试输出Array
22 | void OutPutArray(int* array, int len)
23 | {
24 | for(int i = 0; i < len; i++)
25 | {
26 | printf("array[%d] = %d\n", i, array[i]);
27 | }
28 | return;
29 | }
30 |
31 | void PreOrderTraverse(BiTree binaryTree, int* array, int* pos)
32 | {
33 | if (binaryTree == NULL) {
34 | return;
35 | }
36 |
37 | PushBack(array, pos, binaryTree->data);
38 | PreOrderTraverse(binaryTree->lchild, array, pos);
39 | PreOrderTraverse(binaryTree->rchild, array, pos);
40 |
41 | return;
42 | }
43 |
44 | void BiTreeInsertToArray(BiTree binaryTree, int* array)
45 | {
46 | int pos = 0;
47 | PreOrderTraverse(binaryTree, array, &pos);
48 | OutPutArray(array, pos);
49 |
50 | return;
51 | }
52 |
53 | /**********************
54 | 测试代码框架
55 | 二叉树结构：
56 | 1
57 | / \
58 | 2 3
59 | / \ /
60 | 4 5 6
61 | /
62 | 7
63 | **********************/
64 |
65 | // 程序执行即结束，free
66 | BiTree CreateBiTree()
67 | {
68 | // 1
69 | BiTree tree = NULL;
70 | tree = (BiTNode*)malloc(sizeof(BiTNode));
71 | tree->data = 1;
72 |
73 | // 2、3
74 | BiTree tree_2 = (BiTNode*)malloc(sizeof(BiTNode));
75 | tree_2->data = 2;
76 | BiTree tree_3 = (BiTNode*)malloc(sizeof(BiTNode));
77 | tree_3->data = 3;
78 | tree->lchild = tree_2, tree->rchild = tree_3;
79 | tree_3->rchild = NULL;
80 |
81 | // 4、5
82 | BiTree tree_4 = (BiTNode*)malloc(sizeof(BiTNode));
83 | tree_4->data = 4;
84 | BiTree tree_5 = (BiTNode*)malloc(sizeof(BiTNode));
85 | tree_5->data = 5;
86 | tree_2->lchild = tree_4, tree_2->rchild = tree_5;
87 |
88 | tree_4->rchild = NULL;
89 | tree_5->lchild = NULL, tree_5->rchild = NULL;
90 |
91 | // 6
92 | BiTree tree_6 = (BiTNode*)malloc(sizeof(BiTNode));
93 | tree_6->data = 6;
94 | tree_3->lchild = tree_6;
95 |
96 | tree_6->lchild = NULL, tree_6->rchild = NULL;
97 |
98 | // 7
99 | BiTree tree_7 = (BiTNode*)malloc(sizeof(BiTNode));
100 | tree_7->data = 7;
101 | tree_4->lchild = tree_7;
102 | tree_7->lchild = NULL, tree_7->rchild = NULL;
103 |
104 | return tree;
105 | }
106 |
107 | int main()
108 | {
109 | BiTree tree = CreateBiTree();
110 | int array[ARRAY_MAX_SIZE];
111 |
112 | // 预期输出： 1 2 4 7 5 3 6 ---> 前序遍历
113 | BiTreeInsertToArray(tree, array);
114 |
115 | return 0;
116 | }
--------------------------------------------------------------------------------
/【OS】操作系统/56 IO 管理2-设备与磁盘管理.md:
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/【OS】操作系统/README.md:
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1 | #索引 #操作系统
2 | # 操作系统基本知识
3 | # Ch01. 操作系统概述
4 | - [41 操作系统概要、功能特征与发展演变](41%20操作系统概要、功能特征与发展演变.md)
5 | - [42 操作系统运行机制、中断与异常、系统调用、体系结构](42%20操作系统运行机制、中断与异常、系统调用、体系结构.md)
6 |
7 | # Ch02. 进程管理
8 | - [43 进程管理1-进程切换、进程组织和管理](43%20进程管理1-进程切换、进程组织和管理.md)
9 | - [44 进程管理2-进程间通信、多线程](44%20进程管理2-进程间通信、多线程.md)
10 | - [45 进程管理3-进程调度](45%20进程管理3-进程调度.md)
11 | - [46 进程管理4-调度算法](46%20进程管理4-调度算法.md)
12 | - [47 进程管理5-进程互斥、进程同步机制](47%20进程管理5-进程互斥、进程同步机制.md)
13 | - [48 进程管理6-生产者与消费者问题](48%20进程管理6-生产者与消费者问题.md)
14 | - [49 进程管理7-死锁](49%20进程管理7-死锁.md)
15 |
16 | # Ch03. 内存管理
17 | - [50 内存管理1-覆盖、交换、内存分配](50%20内存管理1-覆盖、交换、内存分配.md)
18 | - [51 内存管理2-分页存储](51%20内存管理2-分页存储.md)
19 | - [52 内存管理3-分段存储](52%20内存管理3-分段存储.md)
20 |
21 | # Ch04. 文件管理
22 | - [53 文件管理1-逻辑结构和物理结构](53%20文件管理1-逻辑结构和物理结构.md)
23 | - [54 文件管理2-文件操作与层次结构](54%20文件管理2-文件操作与层次结构.md)
24 |
25 | # Ch05. IO 管理
26 | - [55 IO 管理1-IO系统组成](55%20IO%20管理1-IO系统组成.md)
27 | - [56 IO 管理2-设备与磁盘管理](56%20IO%20管理2-设备与磁盘管理.md)
28 |
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/工具链/Cmake/src/.gitignore:
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1 | .obsidian
2 | .vscode
3 | */build/*
4 | .vault-stats
5 | *.exe
6 |
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/工具链/Cmake/src/ProjDemo/CMakeLists.txt:
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1 | # 指定最低执行的Cmake版本
2 | cmake_minimum_required(VERSION 3.20)
3 |
4 | # 指定工程名
5 | project(ProjDemo)
6 |
7 | # 指定构建
8 | add_executable(ProjDemo main.cpp)
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/工具链/Cmake/src/ProjDemo/main.cpp:
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1 | #include <iostream>
2 |
3 | int main(void)
4 | {
5 | std::cout << "hello world! " << std::endl;
6 | return 0;
7 | }
8 |
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