CEIA

说明：  KMP算法的具体实现，能够在O(n+m)时间内找出字串在父串中的位置，n为父串长度，m为字串长度(KMP in the proposed algorithm, can be O (n+ m) time to find the string in the parent string position, n the parent string length, m for the string length)

已知二叉树的先序遍历结果，建立二叉树并输出其先序、中序、后序遍历结果(Build a binary tree and print the results of preorder, midorder and postorder traversals based on the known result of preorder traversal)

排序，各种排序算法，插入排序，冒泡排序，快速排序，等等！(Sorting, various sorting algorithms, insertion sort, bubble sort, quick sort, and more!)

迷宫问题c源代码，大小为8*8的迷宫。主函数中输入开始位置和结束位置的坐标，输出所有可能的路径(Maze c source code, size 8* 8 of the maze. Enter the start the main function of the coordinates of the position and end position, the output of all possible paths)

采用Kruskal算法求最小生成树主要数据结构 edgeset GE 存放图中的所有边 int n,int e 存放图中的顶点数与边数 edgeset C 存放生成树中的边 vexlist gv 图中结点的顶点值 adjmatrix s 用来处理图中结点的查找与合并 int m1,m2 一条边上两顶点所属集合的序号 int k 最小生成树中的边数 int d //图中待扫描边元素的下标(For the Minimum Spanning Tree by Kruskal main data structures edgeset GE store all edges in the figure int n, int e store graph vertices and edges edgeset C storage spanning tree edges in the vexlist gv graph node vertex values ​ ​ adjmatrix s used to process graph node to find and merge int m1, m2 an edge belongs to the set number two vertices int k minimum spanning tree edges int d // figure to be Scan edge element subscript)

选择排序的实现，是一种基本的排序方法，但是时间复杂度相对较大。(Select Sort realization, is sort of a basic, but relatively large time complexity.)

题意:给你n个数,求出两两组合的最大公约数 类似打素数表的做法 (Meaning of the questions: to give you the number n, find greatest common divisor of a similar combination twenty-two hit the practice table of prime numbers)

设有一头指针为L的带有表头结点的非循环双向链表，其每个结点中除有prev（前驱指针），data（数据）和next（后继指针）域外，还有一个访问频度域freq。在链表被起用前，其值均初始化为零。每当在链表中进行一次Locate(L,x)运算时，令元素值为x的结点中freq域的值增1，并使此链表中结点保持按访问频度非增（递减）的顺序排列，同时最近访问的结点排在频度相同的结点的最后，以便使频繁访问的结点总是靠近表头。试编写符合上述要求的Locate(L,x)运算的算法，该运算为函数过程，返回找到结点的地址，类型为指针型。(Has a head pointer is non-circular doubly linked list L with a header node, each node in addition to prev (precursor pointer), data (data) and next (successor pointers) outside, there is an access frequency degree domain freq. Before the list was hired, their values are initialized to zero. Whenever carried out in the list once Locate (L, x) when the operation, so that the element node x is the value in freq domain by one, and keep this list in the node-access frequency of non-increasing (decreasing) the order, while a recent visit to the nodes in the same row of the frequency of the last node, so that the nodes are frequently accessed tables are always near the head. Locate (L, x) algorithm is prepared in accordance with the above requirements of the test operation, the operation as a function of the process, return to find the address of the node of type pointer.)

哈夫曼树可以使读者快速方便的查找所需文件(Huffman tree allows readers to quickly and easily find the file)

A*算法通过启发式探索下一结点，逐步逼近目标结点，且使得路径最短。(A* algorithm heuristic to explore the next node, and gradually approaching the target node, and that the shortest path.)