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中文文档

Description

Given two strings word1 and word2, return the minimum number of operations required to convert word1 to word2.

You have the following three 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')

 

Constraints:

  • 0 <= word1.length, word2.length <= 500
  • word1 and word2 consist of lowercase English letters.

Solutions

Solution 1: Dynamic Programming

We define f [ i ] [ j ] as the minimum number of operations to convert w o r d 1 of length i to w o r d 2 of length j . f [ i ] [ 0 ] = i , f [ 0 ] [ j ] = j , i [ 1 , m ] , j [ 0 , n ] .

We consider f [ i ] [ j ] :

  • If w o r d 1 [ i 1 ] = w o r d 2 [ j 1 ] , then we only need to consider the minimum number of operations to convert w o r d 1 of length i 1 to w o r d 2 of length j 1 , so f [ i ] [ j ] = f [ i 1 ] [ j 1 ] ;
  • 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 .

Finally, we can get the state transition equation:

f [ i ] [ j ] = { i , if  j = 0 j , if  i = 0 f [ i 1 ] [ j 1 ] , if  w o r d 1 [ i 1 ] = w o r d 2 [ j 1 ] min ( f [ i 1 ] [ j ] , f [ i ] [ j 1 ] , f [ i 1 ] [ j 1 ] ) + 1 , otherwise

Finally, we return f [ m ] [ n ] .

The time complexity is O ( m × n ) , and the space complexity is O ( m × n ) . m and n are the lengths of w o r d 1 and w o r d 2 respectively.

Python3

class Solution:
    def minDistance(self, word1: str, word2: str) -> int:
        m, n = len(word1), len(word2)
        f = [[0] * (n + 1) for _ in range(m + 1)]
        for j in range(1, n + 1):
            f[0][j] = j
        for i, a in enumerate(word1, 1):
            f[i][0] = i
            for j, b in enumerate(word2, 1):
                if a == b:
                    f[i][j] = f[i - 1][j - 1]
                else:
                    f[i][j] = min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1
        return f[m][n]

Java

class Solution {
    public int minDistance(String word1, String word2) {
        int m = word1.length(), n = word2.length();
        int[][] f = new int[m + 1][n + 1];
        for (int j = 1; j <= n; ++j) {
            f[0][j] = j;
        }
        for (int i = 1; i <= m; ++i) {
            f[i][0] = i;
            for (int j = 1; j <= n; ++j) {
                if (word1.charAt(i - 1) == word2.charAt(j - 1)) {
                    f[i][j] = f[i - 1][j - 1];
                } else {
                    f[i][j] = Math.min(f[i - 1][j], Math.min(f[i][j - 1], f[i - 1][j - 1])) + 1;
                }
            }
        }
        return f[m][n];
    }
}

C++

class Solution {
public:
    int minDistance(string word1, string word2) {
        int m = word1.size(), n = word2.size();
        int f[m + 1][n + 1];
        for (int j = 0; j <= n; ++j) {
            f[0][j] = j;
        }
        for (int i = 1; i <= m; ++i) {
            f[i][0] = i;
            for (int j = 1; j <= n; ++j) {
                if (word1[i - 1] == word2[j - 1]) {
                    f[i][j] = f[i - 1][j - 1];
                } else {
                    f[i][j] = min({f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]}) + 1;
                }
            }
        }
        return f[m][n];
    }
};

Go

func minDistance(word1 string, word2 string) int {
	m, n := len(word1), len(word2)
	f := make([][]int, m+1)
	for i := range f {
		f[i] = make([]int, n+1)
	}
	for j := 1; j <= n; j++ {
		f[0][j] = j
	}
	for i := 1; i <= m; i++ {
		f[i][0] = i
		for j := 1; j <= n; j++ {
			if word1[i-1] == word2[j-1] {
				f[i][j] = f[i-1][j-1]
			} else {
				f[i][j] = min(f[i-1][j], min(f[i][j-1], f[i-1][j-1])) + 1
			}
		}
	}
	return f[m][n]
}

func min(a, b int) int {
	if a < b {
		return a
	}
	return b
}

TypeScript

function minDistance(word1: string, word2: string): number {
    const m = word1.length;
    const n = word2.length;
    const f: number[][] = Array(m + 1)
        .fill(0)
        .map(() => Array(n + 1).fill(0));
    for (let j = 1; j <= n; ++j) {
        f[0][j] = j;
    }
    for (let i = 1; i <= m; ++i) {
        f[i][0] = i;
        for (let j = 1; j <= n; ++j) {
            if (word1[i - 1] === word2[j - 1]) {
                f[i][j] = f[i - 1][j - 1];
            } else {
                f[i][j] = Math.min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1;
            }
        }
    }
    return f[m][n];
}

JavaScript

/**
 * @param {string} word1
 * @param {string} word2
 * @return {number}
 */
var minDistance = function (word1, word2) {
    const m = word1.length;
    const n = word2.length;
    const f = Array(m + 1)
        .fill(0)
        .map(() => Array(n + 1).fill(0));
    for (let j = 1; j <= n; ++j) {
        f[0][j] = j;
    }
    for (let i = 1; i <= m; ++i) {
        f[i][0] = i;
        for (let j = 1; j <= n; ++j) {
            if (word1[i - 1] === word2[j - 1]) {
                f[i][j] = f[i - 1][j - 1];
            } else {
                f[i][j] = Math.min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1;
            }
        }
    }
    return f[m][n];
};

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