- 确定dp数组以及下标的含义:以i-1为结尾的字符串word1,和以j-1位结尾的字符串word2,想要达到相等,所需要删除元素的最少次数。
- 递推公式:当word1[i - 1] 与 word2[j - 1]相同的时候,dp[i][j] = dp[i - 1][j - 1];当word1[i - 1] 与 word2[j - 1]不相同的时候,递推公式可简化为:dp[i][j] = min(dp[i - 1][j] + 1, dp[i][j - 1] + 1);
- 数组初始化:dp[i][0]:word2为空字符串,以i-1为结尾的字符串word1要删除多少个元素,才能和word2相同呢,很明显dp[i][0] = i。dp[0][j]的话同理;
- 遍历顺序:从递推公式 dp[i][j] = min(dp[i - 1][j - 1] + 2, min(dp[i - 1][j], dp[i][j - 1]) + 1); 和dp[i][j] = dp[i - 1][j - 1]可以看出dp[i][j]都是根据左上方、正上方、正左方推出来的。所以遍历的时候一定是从上到下,从左到右,这样保证dp[i][j]可以根据之前计算出来的数值进行计算。
class Solution {
public int minDistance(String word1, String word2) {
int len1 = word1.length();
int len2 = word2.length();
int[][] dp = new int[len1 + 1][len2 + 1];
for (int i = 1; i <= len1; i++) {
for (int j = 1; j <= len2; j++) {
if (word1.charAt(i - 1) == word2.charAt(j - 1)) {
dp[i][j] = dp[i - 1][j - 1] + 1;
} else {
dp[i][j] = Math.max(dp[i - 1][j], dp[i][j - 1]);
}
}
}
return len1 + len2 - dp[len1][len2] * 2;
}
}
class Solution {
public int minDistance(String word1, String word2) {
int m = word1.length();
int n = word2.length();
int[][] dp = new int[m+1][n+1];
for(int i = 1; i <= m; i ++){
dp[i][0] = i;
}
for(int j = 1; j <= n; j ++){
dp[0][j] = j;
}
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(Math.min(dp[i - 1][j - 1], dp[i][j - 1]), dp[i - 1][j]) + 1;
}
}
}
return dp[m][n];
}
}