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关于C语言的一些指针的处理算法，能够使得初学者对C语言指针有自己的了解(Some pointers on C language processing algorithms, it is possible to make a beginner C language pointer has its own understanding)

矩阵运算器，c语言编程，数据结构，免费下载(Matrix calculator, c language programming, data structures, free download)

键盘任意输入一组字母或数字生成无序数组，对数组按ASCII顺序进行排序（排序要求至少用两种排序算法），再从键盘输入一个值进行二分查找，返回查找成功或者失败的信息(Keyboard input and a group of letters, or any number of arrays, and generate disordered array sort order according to the ASCII at least two requirements (sort of), sorting algorithms from the keyboard input a value dichotomy, returns to find success or failure of the information)

数据结构与算法分析的 C++检索代码，很经典(the code of Data structure)

读取数据，统计所得到的文件中每个字母的权值，创建哈夫曼树，哈夫曼编码。哈夫曼解码，解码后内容写入到指定的文件。 读取数据里面的内容是由英文单词组成。读取文件的时候传入文件存放的路径、读取方式以及读出以后存放的数组，最终可以得到一个存放目标文件内容的数组。 将得到的数组进行字母权值的统计，统计每个字母出现的次数，次数即为每个字母的权值。 将得到的字符数组与权值数组作为创建哈夫曼树的依据，哈夫曼树根据每个字母权值的大小来创建，每个节点，包括权值、父节点、左子、右子和字母本身。 根据哈夫曼树进行编码。形成目标文件的哈夫曼编码，将此编码返回。 根据哈夫曼树得到的数组即为解码数组，解码数组作为解码的结果返回。 写入输出文件，将解码得到的数组、文件的完整路径以及文件的写方式作为参数传入，将数组写入到相应的文件中。 (Read the data, statistical documents obtained weights for each letter, create a Huffman tree, Huffman coding. Huffman decoding, the decoded contents are written to the specified file. Read the content inside is composed of English words. When the incoming file to read the file storage path, read mode and read out after storage array that can eventually get a storage target file contents of the array. The resulting array of letter weights statistics, statistical number of occurrences of each letter, the number is the weight of each letter. The resulting character array with the weights array as the basis for creating Huffman tree, Huffman tree based on the size of the weights of each letter to create, for each node, including weights, parent, left child, right child, and letter itself. According to Huffman coding. The formation of the target file Huffman coding, this code returns. According to Huffman decoding the resulting array is an array, the decoder decodes the result is retur)

一．问题描述 对2006年度全国80多个城市的每天空气质量状况进行查询、排序等操作。 空气质量状况对象包括城市代码、城市名称、首要污染物、污染指数、污染物级别、空气状况、年、月、日 二、实验要求 1． 普通查询：输入城市名称和城市代码，分别查询该城市每天、每周、每月、每季度和全年的空气质量状况 例子：查询太原市2006年第8周的空气质量状况 2．统计查询： （1）输入城市名称和城市代码，分别查询该城市每周、每月、每季度和全年的空气质量为优、良、轻微污染、轻度污染、重污染的天数 例子：查询石家庄市2006年第2季度空气质量为轻微污染的总天数 （2）根据时间查询空气质量状况：输入周编号、月编号、季度编号或年编号，以及空气质量为优、良、轻微污染、轻度污染、重污染的天数，查找相应的城市名称 例子：查询2006年5月，空气被轻度污染3天以上的城市有哪些？ 3．排序查询 （1）输入周编号、月编号、季度编号或年编号，查询城市空气质量的排行榜 例子：查询2006年第6周，全国空气平均质量最好的前20个城市为哪些？ 三、数据文件 Data.txt(one. Problem Description of the air quality day in 2006 more than 80 cities nationwide query, sorting and other operations. Air Quality objects include city code, city name, the primary pollutant, pollution index, contaminant level, air condition, year, month, day two, experimental requirements 1. General Queries: Enter a city name and city codes, each query in the city daily, weekly, monthly, quarterly example air quality and full year: Queries air quality in Taiyuan first eight weeks of 2006 2. Statistical inquiry: (1) enter a city name and city codes, each query in the city weekly, monthly, quarterly and annual air quality as excellent, good, slight pollution, light pollution, heavy pollution days example: inquiry Shijiazhuang City in 2006 second quarter, the air quality is the total number of days a slight pollution (2) according to time of the query air quality conditions: enter the week number, month number, quarter number or in number, and the air quality is excellent, good, sli)

数据结构课程设计，在VC环境下完成，利用哈夫曼树原理，主要功能是实现字符的压缩和解压缩，设计脉络清晰，易懂(Data structure course design, completed in the VC environment, using Huffman tree principle, the main function is to achieve the character of the compression and decompression, design, clear structure, easy to understand)

约瑟夫问题，用数据结构的循环链表实现约瑟夫问题的解答(Joseph problems，30 people in a circle, and inspires us with a circular chain to said. Can use structure array to make a cycle chain. The structure has two members, one for pointing down a pointer to a circular chain )

some problems about c++.(car.cpp)

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)