原创

查找过程演示：

在数组[130,150,170,190,210,230,250,270,290,310]中查找数字190，红色为二分线(折半线)，灰色为查找区域，黑色为排除区域。

SYJ二分查找演示.gif

二分查找优缺点：

二分查找(折半查找)优点是比较次数少，查找速度快，平均性能好；其缺点是要求待查表为有序表，且插入删除困难。时间复杂度可以表示O(h)=O(log2n)，以2为底，n的对数。比如数组长度为10，最多找4次。

objectIve-c实现代码：

#import <Foundation/Foundation.h>

int search(NSArray *array,int item){
    int x = 1;
    int low = 0;
    int high = (int)[array count] - 1;
    while (low <= high) {
        NSLog(@"第%d次比较",x);
        x++;
        int mid = (high+low)/2;
        if(item == [array[mid] intValue]){
            NSLog(@"%d找到了,在第%d个位置",item,mid);
            return mid;
        }else if(item < [array[mid] intValue]){
            NSLog(@"%d比%d大，继续查找",[array[mid] intValue],item);
            high = mid-1;
        }else{
            NSLog(@"%d比%d小，继续查找",[array[mid] intValue],item);
            low = mid+1;
        }
    }
    return -1;
}

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSLog(@"请输入要查询的数字:");
        int x;
        scanf("%d",&x);
        NSArray *array = @[@1,@3,@5,@7,@9,@11,@13,@15,@17,@19,@21,@23,@25];
        int jieguo = search(array,x);
        if(jieguo == -1){
            NSLog(@"没找到要查找的数字");
        }
    }
    return 0;
}

运行截图：

1.png

java实现代码：

import java.util.Scanner;
public class PaiXu{
    public static void main(String[] args){
        Integer[] haha = {1,3,5,7,9,11,13,15,17,19,21,23,25,27};
        Scanner sc = new Scanner(System.in);
        System.out.println("请输入您要查找的值：");
        int z = sc.nextInt();
        int y = binarySearch(haha,z);
        if(y == -1){
            System.out.println("要查找的值不存在");
        }
    }

    public static int binarySearch(Integer[] srcArray,int des){
        int x = 1;
        int low = 0;
        int high = srcArray.length-1;
        while(low<=high){
            System.out.println("第"+x+"次比较");
            x++;
            int mid = (high+low)/2;
            if(des == srcArray[mid]){
                System.out.println(des+"找到了,在第"+mid+"个位置");
                return mid;
            }else if(des < srcArray[mid]){
                System.out.println(srcArray[mid]+"比"+des+"大，继续查找");
                high = mid-1;
            }else{
                System.out.println(srcArray[mid]+"比"+des+"小，继续查找");
                low = mid+1;
            }
        }
        return -1;
    }
}

运行截图：

2.png

Python实现代码：

def binary_search(list,item):
    x = 1
    low = 0
    high = len(list)-1
    while low <= high:
        print('第%d次比较'%x)
        x=x+1
        mid = (low+high)//2
        guess = list[mid]
        if guess == item:
            print('找到了,在第%d个位置'%mid)
            return mid
        if guess > item:
            print('%d比%d大，继续查找'%(guess,item))
            high = mid-1
        else:
            print('%d比%d小，继续查找'%(guess,item))
            low = mid+1
    print('找不到%d'%item)
    return None
my_list = [1,3,5,7,9,11,13,15,17,19,21,23,25]
z = int(input('请输入要查找的数字:'))
binary_search(my_list,z)

运行截图：

scala实现代码：

object ErFen{
    def main(args:Array[String]){
        //var z:Array[Int] = new Array[Int](14);
        //var z = new Array[Int](14);
        var z = Array(1,3,5,7,9,11,13,15,17,19,21,23,25,27);
        var y:Int = search(z,15);
        if(y == -1){
            println("要查找的值不存在");
        }
    }

    def search(arr:Array[Int],des:Int):Int={
        var x:Int = 1;
        var low:Int = 0;
        var high:Int = arr.length-1;
        while(low <= high){
            println("第"+x+"次比较");
            x += 1;
            var mid:Int = (high+low)/2;
            if(des == arr(mid)){
                println(des+"找到了，在第"+mid+"个位置");
                return mid;
            }else if(des < arr(mid)){
                println(arr(mid)+"比"+des+"大，继续查找");
                high = mid - 1;
            }else{
                println(arr(mid)+"比"+des+"小，继续查找");
                low = mid + 1;
            }
        }
        return -1;
    }
}

运行截图：

Snip20170602_4.png