法1:DP
本质是不带替换操作的最小编辑距离问题!!!
Python
class Solution:
def minDistance(self, word1: str, word2: str) -> int:
m, n = len(word1), len(word2)
dp = [[0]*(n+1) for _ in range(m+1)]
for i in range(m+1):
dp[i][0] = i
for j in range(n+1):
dp[0][j] = j
for i in range(1, m+1):
for j in range(1, n+1):
if word1[i-1] == word2[j-1]:
dp[i][j] = dp[i-1][j-1]
else:
dp[i][j] = min(dp[i][j-1], dp[i-1][j]) + 1
return dp[m][n]
Java
class Solution {
public int minDistance(String word1, String word2) {
int m = word1.length() + 1, n = word2.length() + 1;
int[][] dp = new int[m][n];
for (int i = 1; i < n; ++i) { // 首行
dp[0][i] = i;
}
for (int i = 1; i < m; ++i) { // 首列
dp[i][0] = i;
}
for (int i = 1; i < m; ++i) {
for (int j = 1; j < n; ++j) {
if (word1.charAt(i - 1) == word2.charAt(j - 1)) {
dp[i][j] = dp[i - 1][j - 1];
} else {
dp[i][j] = Math.min(dp[i - 1][j], dp[i][j - 1]) + 1;
}
}
}
return dp[m - 1][n - 1];
}
}