LeetCode 72. Edit Distance 编辑距离 (C++/Java)
题目:
Given two words word1 and word2, find the minimum number of operations required to convert word1 to word2.
You have the following 3 operations permitted on a word:
- Insert a character
- Delete a character
- Replace a character
Example 1:
Input: word1 = "horse", word2 = "ros"
Output: 3
Explanation:
horse -> rorse (replace 'h' with 'r')
rorse -> rose (remove 'r')
rose -> ros (remove 'e')
Example 2:
Input: word1 = "intention", word2 = "execution"
Output: 5
Explanation:
intention -> inention (remove 't')
inention -> enention (replace 'i' with 'e')
enention -> exention (replace 'n' with 'x')
exention -> exection (replace 'n' with 'c')
exection -> execution (insert 'u')
分析:
给定两个单词,求word1转换到word2需要的最少步骤,转换的操作有三种,分别是插入一个字符,删除一个字符,替换一个字符。
d(word1, word2)用来求两个单词转换的需要的最小步数,那么如果当两个单词的最后一个字符是相同的,则d(word1, word2) = d(word1', word2')其word1'和word2'是分别去掉最后一个字符的单词。
如果最后两个字符不相同时,我们就需要操作来进行转换,一种是在word1后增加一个字符,是其最后一个字符和word2的最后一个字符相同,一种是删去word1的最后一个字符,一种是将word1的最后一个字符转换成word2的最后一个字符,那么此时最小的步数就是前三个操作的最小值加上1.
可能有同学会问为什么不在word2上进行操作,实际上操作转换这一步是有5个子问题的,但实际上在word1后增加一个字符和word2最后字符相同,相当于在word2后删除字符;删去word1的字符相当于在word2后增加一个字符和word1最后字符相同;而转换操作明显是一样的,所以就合并成为了三个子问题。
当递归执行到其中一个串为空串时,则加上另一个串的长度即可,相当于删去所有的字符。
程序:
C++
class Solution {
public:
int minDistance(string word1, string word2) {
int l1 = word1.length();
int l2 = word2.length();
dp = vector<vector<int>>(l1+1, vector<int>(l2+1, -1));
return minDistance(word1, word2, l1, l2);
}
private:
vector<vector<int>> dp;
int minDistance(string& word1, string& word2, int l1, int l2){
if(l1 == 0)
return l2;
if(l2 == 0)
return l1;
if(dp[l1][l2] >= 0)
return dp[l1][l2];
int res = 0;
if(word1[l1-1] == word2[l2-1]){
res = minDistance(word1, word2, l1-1, l2-1);
dp[l1][l2] = res;
return res;
}
res = min(minDistance(word1, word2, l1-1, l2),
min(minDistance(word1, word2, l1, l2-1),
minDistance(word1, word2, l1-1, l2-1))) + 1;
dp[l1][l2] = res;
return res;
}
};
Java
class Solution {
public int minDistance(String word1, String word2) {
int l1 = word1.length();
int l2 = word2.length();
dp = new int[l1+1][l2+1];
for(int i = 0; i < dp.length; ++i){
for(int j = 0; j < dp[i].length; ++j){
dp[i][j] = -1;
}
}
return minDistance(word1, word2, l1, l2);
}
private int minDistance(String word1, String word2, int l1, int l2){
if(l1 == 0) return l2;
if(l2 == 0) return l1;
if(dp[l1][l2] >= 0)
return dp[l1][l2];
int res = 0;
if(word1.charAt(l1-1) == word2.charAt(l2-1)){
res = minDistance(word1, word2, l1-1, l2-1);
}else{
res = Math.min(minDistance(word1, word2, l1-1, l2),
Math.min(minDistance(word1, word2, l1, l2-1),
minDistance(word1, word2, l1-1, l2-1))) + 1;
}
dp[l1][l2] = res;
return res;
}
private int[][] dp;
}
LeetCode 72. Edit Distance 编辑距离 (C++/Java)的更多相关文章
- [LeetCode] 72. Edit Distance 编辑距离
Given two words word1 and word2, find the minimum number of operations required to convert word1 to ...
- leetCode 72.Edit Distance (编辑距离) 解题思路和方法
Edit Distance Given two words word1 and word2, find the minimum number of steps required to convert ...
- [LeetCode] 72. Edit Distance(最短编辑距离)
传送门 Description Given two words word1 and word2, find the minimum number of steps required to conver ...
- 【LeetCode】72. Edit Distance 编辑距离(Python & C++)
作者: 负雪明烛 id: fuxuemingzhu 个人博客: http://fuxuemingzhu.cn/ 目录 题目描述 题目大意 解题方法 递归 记忆化搜索 动态规划 日期 题目地址:http ...
- LeetCode - 72. Edit Distance
最小编辑距离,动态规划经典题. Given two words word1 and word2, find the minimum number of steps required to conver ...
- [leetcode]72. Edit Distance 最少编辑步数
Given two words word1 and word2, find the minimum number of operations required to convert word1 to ...
- 72. Edit Distance(编辑距离 动态规划)
Given two words word1 and word2, find the minimum number of operations required to convert word1 to ...
- 第十八周 Leetcode 72. Edit Distance(HARD) O(N^2)DP
Leetcode72 看起来比较棘手的一道题(列DP方程还是要大胆猜想..) DP方程该怎么列呢? dp[i][j]表示字符串a[0....i-1]转化为b[0....j-1]的最少距离 转移方程分三 ...
- [leetcode] 72. Edit Distance (hard)
原题 dp 利用二维数组dp[i][j]存储状态: 从字符串A的0~i位子字符串 到 字符串B的0~j位子字符串,最少需要几步.(每一次删增改都算1步) 所以可得边界状态dp[i][0]=i,dp[0 ...
- 【Leetcode】72 Edit Distance
72. Edit Distance Given two words word1 and word2, find the minimum number of steps required to conv ...
随机推荐
- 力扣614(MySQL)-二级关注者(中等)
题目: 在 facebook 中,表 follow 会有 2 个字段: followee, follower ,分别表示被关注者和关注者. 请写一个 sql 查询语句,对每一个关注者,查询关注他的关注 ...
- RocketMQ 之 IoT 消息解析:物联网需要什么样的消息技术?
前言: 从初代开源消息队列崛起,到 PC 互联网.移动互联网爆发式发展,再到如今 IoT.云计算.云原生引领了新的技术趋势,消息中间件的发展已经走过了 30 多个年头. 目前,消息中间件在国内许多行业 ...
- What's new in dubbo-go v1.5.6
简介: dubbogo 社区近期发布了 dubbogo v1.5.6.该版本和 dubbo 2.7.8 对齐,提供了命令行工具,并提供了多种加载配置的方式. 作者 | 铁城 dubbo-go 社区 ...
- 如何开发 Node.js Native Add-on?
简介: 来一起为 Node.js 的 add-on 生态做贡献吧~ 作者 | 吴成忠(昭朗) 这篇文章是由 Chengzhong Wu (@legendecas),Gabriel Schulhof ( ...
- [FAQ] swagger-php @OA\JsonContent 与 @MediaType @OA\Schema 的用法
@OA\JsonContent 是对 @MediaType @OA\Schema 两者的封装,类似于 laravel 中 JsonResponse 对 Response 的封装. @OA\JsonCo ...
- 2018-2-13-C#-获得设备usb信息
title author date CreateTime categories C# 获得设备usb信息 lindexi 2018-2-13 17:23:3 +0800 2018-2-13 17:23 ...
- 7.deployment扩容-查看pod使用的CPU-统计ready状态节点数量
官方文档:https://kubernetes.io/zh-cn/docs/tasks/run-application/scale-stateful-set/题目1: 将名为loadbalancer的 ...
- Fastbin attack&&Double free和Unsortbin leak的综合使用
Fastbin attack&&Double free和Unsortbin leak的综合使用 今天做一个综合题目,包括利用Fastbin attack实现多指针指向一个地址,以及利用 ...
- vue使用bus.js在兄弟组件传值
A组件往B组件传递数据data 1.src下创建文件eventBus.js,内容: import Vue from 'vue' export default new Vue() 2.在A,B组件分别引 ...
- Oracle修改字段长度及属性
首发微信公众号:SQL数据库运维 原文链接:https://mp.weixin.qq.com/s?__biz=MzI1NTQyNzg3MQ==&mid=2247486117&idx=1 ...