Java算法之字符串反转分析

本文来自http://blog.csdn.net/liuxian13183/ ，引用必须注明出处！

在基本的工作内容开发中，算法不会显得那么重要，而在百万级别的时候，差距非常大，今天带大家研究下常见的字符串反转算法。

public class StringReverse {

	public static String reverse1(String orig) {

		char[] s = orig.toCharArray();

		int n = s.length - 1;

		int halfLength = n / 2;

		for (int i = 0; i <= halfLength; i++) {// 2分法+替换算法

			char temp = s[i];

			s[i] = s[n - i];

			s[n - i] = temp;

		}

		return new String(s);

	}

	public static String reverse2(String s) {// 2分法+异或算法

		char[] str = s.toCharArray();

		int begin = 0;

		int end = s.length() - 1;

		while (begin < end) {

			str[begin] = (char) (str[begin] ^ str[end]);

			str[end] = (char) (str[begin] ^ str[end]);

			str[begin] = (char) (str[end] ^ str[begin]);

			begin++;

			end--;

		}

		return new String(str);

	}

	public static String reverse3(String s) {// jdk提供

		return new StringBuffer(s).reverse().toString();

	}

	public static String reverse4(String s) {// 2分递归算法

		int length = s.length();

		if (length <= 1)

			return s;

		String left = s.substring(0, length / 2);

		String right = s.substring(length / 2, length);

		return reverse1(right) + reverse1(left);

	}

	public static String reverse5(String s) {// 傳統从后往前加

		int length = s.length();

		String reverse = "";

		for (int i = 0; i < length; i++)

			reverse = s.charAt(i) + reverse;

		return reverse;

	}

	public static String reverse6(String s) {//傳統與5雷同

		char[] array = s.toCharArray();

		String reverse = "";

		for (int i = array.length - 1; i >= 0; i--)

			reverse += array[i];

		return reverse;

	}

	public static String reverse7(String s) {// 利用栈先进后出的特性

		char[] str = s.toCharArray();

		Stack<Character> stack = new Stack<Character>();

		for (int i = 0; i < str.length; i++)

			stack.push(str[i]);

		String reversed = "";

		for (int i = 0; i < str.length; i++)

			reversed += stack.pop();

		return reversed;

	}

	public static void main(String[] args) {

		String str = "hello world !";

		int length = 10000000;

		long curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse1(str);

		}

		System.out.println("reverse1:" + (System.currentTimeMillis() - curTime));

		curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse2(str);

		}

		System.out.println("reverse2:" + (System.currentTimeMillis() - curTime));

		curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse3(str);

		}

		System.out.println("reverse3:" + (System.currentTimeMillis() - curTime));

		curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse4(str);

		}

		System.out.println("reverse4:" + (System.currentTimeMillis() - curTime));

		curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse5(str);

		}

		System.out.println("reverse5:" + (System.currentTimeMillis() - curTime));

		curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse6(str);

		}

		System.out.println("reverse6:" + (System.currentTimeMillis() - curTime));

		curTime = System.currentTimeMillis();

		for (int i = 0; i < length; i++) {

			reverse7(str);

		}

		System.out.println("reverse7:" + (System.currentTimeMillis() - curTime));

	}

}

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" alt="" />

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