七种常见的排序算法的C++实现

来源：互联网发布：马航mh370真相知乎编辑：程序博客网时间：2024/05/29 19:15
因为几个算法使用了递归，这里测试用的数组大小又比较大，如果使用vs编译的话，需要调整一下堆栈的大小，否则容易发生stackOverflow的错误。
运行效果
代码如下
#include"stdafx.h"#include<iostream>#include<ctime>#include<cstdlib>using namespace std;#define NUM 50000;void bubbleSort(int temp1[], int length);void insertSort(int temp2[], int length);void shellSort(int temp3[], int length);void selectSort(int temp4[], int length);void mergeSort(int temp5[], int left, int right);void quickSort(int temp6[], int left, int right);void heapSort(int temp7[], int length);void heapRebuild(int arr[], int root, int size);int main(){    int length = 50000;    int arr[50000];    srand(time(0));    for (int i = 0; i<length; i++)    {        arr[i] = rand() % NUM;    }    int temp1[50000];    int temp2[50000];    int temp3[50000];    int temp4[50000];    int temp5[50000];    int temp6[50000];       int temp7[50000];    int copySize = length * 4;    memcpy(temp1, arr, copySize);    memcpy(temp2, arr, copySize);    memcpy(temp3, arr, copySize);    memcpy(temp4, arr, copySize);    memcpy(temp5, arr, copySize);    memcpy(temp6, arr, copySize);    memcpy(temp7, arr, copySize);    bubbleSort(temp1, length);    insertSort(temp2, length);    shellSort(temp3, length);    selectSort(temp4, length);    clock_t start = clock();    mergeSort(temp5, 0, length-1);    clock_t end = clock();    cout << "Time taken by mergeSort:\t" << (double)(end - start) << " milliseconds" << endl;    clock_t start1 = clock();    quickSort(temp6, 0, length - 1);    clock_t end1 = clock();    cout << "Time taken by quickSort:\t" << (double)(end1 - start1) << " milliseconds" << endl;    clock_t start2 = clock();    heapSort(temp7, length);    clock_t end2 = clock();    cout << "Time taken by heapSort:\t" << (double)(end2 - start2) << " milliseconds" << endl;    getchar();    return 0;}//冒泡排序void bubbleSort(int temp1[], int length){    int i, j, temp;    clock_t start = clock();    for (i = 0; i<length; i++)    {        for (j = 1; j<length - i; j++)        {            if ((*(temp1 + j - 1))>(*(temp1 + j)))            {                temp = (*(temp1 + j));                (*(temp1 + j)) = (*(temp1 + j - 1));                (*(temp1 + j - 1)) = temp;            }        }    }    clock_t end = clock();    cout << "Time taken by bubbleSort:\t" << (double)(end - start) / CLOCKS_PER_SEC << "seconds" << endl;}//插入排序void insertSort(int temp2[], int length)//有数组的地方需要考虑边界{    int i, j, temp, k, l;    clock_t start = clock();    for (i = 0; i<length; i++)    {        for (j = i - 1; j >= 0; j--)//结束之后，j=-1,如果没有break。        {            if ((*(temp2 + j))<(*(temp2 + i)))            {                break;            }        }        if (j != i - 1)        {            temp = (*(temp2 + i));            for (k = i - 1; k>j; k--)            {                (*(temp2 + k + 1)) = (*(temp2 + k));            }            (*(temp2 + k + 1)) = temp;        }    }    clock_t end = clock();    cout << "Time taken by insertSort:\t" << (double)(end - start) / CLOCKS_PER_SEC << "seconds" << endl;}//希尔排序;void shellSort(int temp3[], int length){    int i, j;    int temp = 0;    clock_t start = clock();    for (int gap = length / 2; gap>0; gap /= 2)    {        for (int i = gap; i<length; i++)        {            for (j = i - gap; j >= 0 && ((*(temp3 + j))>(*(temp3 + j + gap))); j -= gap)            {                temp = (*(temp3 + j));                (*(temp3 + j)) = (*(temp3 + j + gap));                (*(temp3 + j + gap)) = temp;            }        }    }    clock_t end = clock();    cout << "Time taken by shellSort:\t" << (double)(end - start) / CLOCKS_PER_SEC << "seconds" << endl;}//选择排序;void selectSort(int temp4[], int length){    int i, j, temp, min;    clock_t start = clock();    for (i = 0; i<length; i++)    {        min = i;        for (j = i + 1; j<length; j++)        {            if ((*(temp4 + j))<(*(temp4 + min)))            {                min = j;            }        }        temp = (*(temp4 + i));        (*(temp4 + i)) = (*(temp4 + min));        (*(temp4 + min)) = temp;    }    clock_t end = clock();    cout << "Time taken by selectSort:\t" << (double)(end - start) / CLOCKS_PER_SEC << "seconds" << endl;}//归并排序;void mergeSort(int temp5[], int left, int right){    int temp[50000];    int i, j, k, mid;    if (left<right)    {        mid = (left + right) / 2;        //递归        mergeSort(temp5, left, mid);        mergeSort(temp5, mid + 1, right);        //合并        i = left;        j = mid + 1;        k = 0;        while ((i <= mid) &&(j<= right))        {            if ((*(temp5 + i))<(*(temp5 + j)))            {                temp[k] = (*(temp5 + i));                k++;                i++;            }            else            {                temp[k] = (*(temp5 + j));                k++;                j++;            }        }        while (i <= mid)        {            temp[k] = (*(temp5 + i));            k++;            i++;        }        while (j <= right)        {            temp[k] = (*(temp5 + j));            k++;            j++;        }        for (int l = 0; l<k; l++)            temp5[left + l] = temp[l];    }}//快速排序;void quickSort(int temp6[], int left, int right){    if (left<right)//递归的结束    {        //temp作为第一个基数        int i = left, j = right, temp = *(temp6 + left);        while (i<j)//循环，直到对于基数的一轮交换全部完成        {            while ((i<j) && ((*(temp6 + j)) >= temp))            {                j--;            }            if (i<j)            {                (*(temp6 + i)) = (*(temp6 + j));                i++;            }            while ((i<j) && ((*(temp6 + i))<temp))            {                i++;            }            if (i<j)            {                (*(temp6 + j)) = (*(temp6 + i));                j--;            }        }        (*(temp6 + i)) = temp;//到此，一轮基于基数的交换完成        quickSort(temp6, left, i - 1);//缩小范围，在left到i-1范围内的数都比刚才的基数小，在这个范围内再选出基数做重复交换，不断递归，直到left<right不成立。        quickSort(temp6, i + 1, right);    }}//堆排序;/*堆排序是一种基于二叉堆这个数据结构的排序算法，属于原地排序二叉堆满足二个特性：1．父结点的键值总是大于或等于（小于或等于）任何一个子节点的键值。2．每个结点的左子树和右子树都是一个二叉堆（都是最大堆或最小堆）。*/void heapSort(int temp7[], int length){    for (int i = length / 2; i >= 0; i--)    {        heapRebuild(temp7, i, length);//堆化数组，根节点是数组中最大的数    }    int last = length - 1;    for (int i = 1; i <= length; i++, last--)    {        int temp = *temp7;        *temp7 = *(temp7 + last);        *(temp7 + last) = temp;        heapRebuild(temp7, 0, last);//每次都从根节点取走数值，然后缩小范围再重建二叉堆    }}void heapRebuild(int temp7[], int root, int size){    int child = 2 * root + 1;//i结点的父结点下标就为(i – 1) / 2,所以2*root+1是子节点    if (child <= size - 1)    {        int rightChild = child + 1;        int largest = child;        if (rightChild <= size - 1)            if ((*(temp7 + child))<(*(temp7 + rightChild)))                largest = rightChild;        if ((*(temp7 + root))<(*(temp7 + largest)))//根节点的数值如果比最大的子节点小，那么就交换他们        {            int temp = (*(temp7 + largest));            (*(temp7 + largest)) = (*(temp7 + root));            (*(temp7 + root)) = temp;            heapRebuild(temp7, largest, size);//递归，原来最大的那个子节点作为下一层递归的根节点        }    }}
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