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Update readme.md
Co-Authored-By: Antim-IWP <203163676+Antim-IWP@users.noreply.github.com> Co-Authored-By: Shiwangi Srivastava <174641070+IamShiwangi@users.noreply.github.com>
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<!-- problem:start -->
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# [72. Edit Distance](https://leetcode.com/problems/edit-distance)
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---
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comments: true
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difficulty: Medium
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edit_url: https://github.com/doocs/leetcode/edit/main/solution/0000-0099/0072.Edit%20Distance/README_EN.md
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tags:
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- String
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- Dynamic Programming
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---
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## Description
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<!-- description:start -->
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<p>Given two strings <code>word1</code> and <code>word2</code>, return <em>the minimum number of operations required to convert <code>word1</code> to <code>word2</code></em>.</p>
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<p>You have the following three operations permitted on a word:</p>
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<ul>
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<li>Insert a character</li>
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<li>Delete a character</li>
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<li>Replace a character</li>
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</ul>
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<p>&nbsp;</p>
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<p><strong class="example">Example 1:</strong></p>
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<pre>
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<strong>Input:</strong> word1 = &quot;horse&quot;, word2 = &quot;ros&quot;
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<strong>Output:</strong> 3
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<strong>Explanation:</strong>
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horse -&gt; rorse (replace &#39;h&#39; with &#39;r&#39;)
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rorse -&gt; rose (remove &#39;r&#39;)
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rose -&gt; ros (remove &#39;e&#39;)
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</pre>
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<p><strong class="example">Example 2:</strong></p>
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<pre>
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<strong>Input:</strong> word1 = &quot;intention&quot;, word2 = &quot;execution&quot;
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<strong>Output:</strong> 5
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<strong>Explanation:</strong>
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intention -&gt; inention (remove &#39;t&#39;)
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inention -&gt; enention (replace &#39;i&#39; with &#39;e&#39;)
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enention -&gt; exention (replace &#39;n&#39; with &#39;x&#39;)
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exention -&gt; exection (replace &#39;n&#39; with &#39;c&#39;)
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exection -&gt; execution (insert &#39;u&#39;)
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</pre>
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<p>&nbsp;</p>
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<p><strong>Constraints:</strong></p>
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<ul>
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<li><code>0 &lt;= word1.length, word2.length &lt;= 500</code></li>
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<li><code>word1</code> and <code>word2</code> consist of lowercase English letters.</li>
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</ul>
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<!-- description:end -->
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## Solutions
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<!-- solution:start -->
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### Solution 1: Dynamic Programming
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We define $f[i][j]$ as the minimum number of operations to convert $word1$ of length $i$ to $word2$ of length $j$. $f[i][0] = i$, $f[0][j] = j$, $i \in [1, m], j \in [0, n]$.
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We consider $f[i][j]$:
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- If $word1[i - 1] = word2[j - 1]$, then we only need to consider the minimum number of operations to convert $word1$ of length $i - 1$ to $word2$ of length $j - 1$, so $f[i][j] = f[i - 1][j - 1]$;
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- Otherwise, we can consider insert, delete, and replace operations, then $f[i][j] = \min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1$.
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Finally, we can get the state transition equation:
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$$
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f[i][j] = \begin{cases}
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i, & \textit{if } j = 0 \\
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j, & \textit{if } i = 0 \\
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f[i - 1][j - 1], & \textit{if } word1[i - 1] = word2[j - 1] \\
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\min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1, & \textit{otherwise}
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\end{cases}
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$$
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Finally, we return $f[m][n]$.
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The time complexity is $O(m \times n)$, and the space complexity is $O(m \times n)$. $m$ and $n$ are the lengths of $word1$ and $word2$ respectively.
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<!-- tabs:start -->
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#### Python3
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```python
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class Solution:
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def minDistance(self, word1: str, word2: str) -> int:
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m, n = len(word1), len(word2)
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f = [[0] * (n + 1) for _ in range(m + 1)]
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for j in range(1, n + 1):
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f[0][j] = j
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for i, a in enumerate(word1, 1):
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f[i][0] = i
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for j, b in enumerate(word2, 1):
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if a == b:
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f[i][j] = f[i - 1][j - 1]
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else:
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f[i][j] = min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1
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return f[m][n]
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```
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#### Java
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```java
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class Solution {
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public int minDistance(String word1, String word2) {
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int m = word1.length(), n = word2.length();
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int[][] f = new int[m + 1][n + 1];
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for (int j = 1; j <= n; ++j) {
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f[0][j] = j;
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}
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for (int i = 1; i <= m; ++i) {
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f[i][0] = i;
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for (int j = 1; j <= n; ++j) {
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if (word1.charAt(i - 1) == word2.charAt(j - 1)) {
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f[i][j] = f[i - 1][j - 1];
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} else {
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f[i][j] = Math.min(f[i - 1][j], Math.min(f[i][j - 1], f[i - 1][j - 1])) + 1;
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}
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}
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}
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return f[m][n];
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}
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}
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```
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#### C++
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```cpp
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class Solution {
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public:
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int minDistance(string word1, string word2) {
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int m = word1.size(), n = word2.size();
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int f[m + 1][n + 1];
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for (int j = 0; j <= n; ++j) {
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f[0][j] = j;
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}
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for (int i = 1; i <= m; ++i) {
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f[i][0] = i;
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for (int j = 1; j <= n; ++j) {
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if (word1[i - 1] == word2[j - 1]) {
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f[i][j] = f[i - 1][j - 1];
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} else {
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f[i][j] = min({f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]}) + 1;
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}
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}
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}
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return f[m][n];
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}
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};
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```
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#### Go
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```go
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func minDistance(word1 string, word2 string) int {
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m, n := len(word1), len(word2)
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f := make([][]int, m+1)
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for i := range f {
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f[i] = make([]int, n+1)
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}
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for j := 1; j <= n; j++ {
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f[0][j] = j
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}
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for i := 1; i <= m; i++ {
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f[i][0] = i
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for j := 1; j <= n; j++ {
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if word1[i-1] == word2[j-1] {
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f[i][j] = f[i-1][j-1]
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} else {
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f[i][j] = min(f[i-1][j], min(f[i][j-1], f[i-1][j-1])) + 1
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}
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}
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}
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return f[m][n]
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}
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```
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#### TypeScript
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```ts
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function minDistance(word1: string, word2: string): number {
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const m = word1.length;
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const n = word2.length;
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const f: number[][] = Array(m + 1)
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.fill(0)
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.map(() => Array(n + 1).fill(0));
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for (let j = 1; j <= n; ++j) {
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f[0][j] = j;
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}
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for (let i = 1; i <= m; ++i) {
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f[i][0] = i;
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for (let j = 1; j <= n; ++j) {
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if (word1[i - 1] === word2[j - 1]) {
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f[i][j] = f[i - 1][j - 1];
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} else {
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f[i][j] = Math.min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1;
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}
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}
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}
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return f[m][n];
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}
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```
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#### JavaScript
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```js
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/**
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* @param {string} word1
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* @param {string} word2
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* @return {number}
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*/
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var minDistance = function (word1, word2) {
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const m = word1.length;
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const n = word2.length;
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const f = Array(m + 1)
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.fill(0)
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.map(() => Array(n + 1).fill(0));
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for (let j = 1; j <= n; ++j) {
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f[0][j] = j;
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}
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for (let i = 1; i <= m; ++i) {
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f[i][0] = i;
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for (let j = 1; j <= n; ++j) {
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if (word1[i - 1] === word2[j - 1]) {
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f[i][j] = f[i - 1][j - 1];
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} else {
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f[i][j] = Math.min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1;
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}
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}
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}
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return f[m][n];
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};
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```
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<!-- tabs:end -->
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<!-- solution:end -->
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<!-- problem:end -->

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