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[LeetCode]Distinct Subsequences,解题报告
题目
Given a string S and a string T, count the number of distinct subsequences of T in S.
A subsequence of a string is a new string which is formed from the original string by deleting some (can be none) of the characters without disturbing the relative positions of the remaining characters. (ie, "ACE" is a subsequence of "ABCDE" while "AEC" is not).
Here is an example:
S = "rabbbit", T = "rabbit"
Return 3.
A subsequence of a string is a new string which is formed from the original string by deleting some (can be none) of the characters without disturbing the relative positions of the remaining characters. (ie, "ACE" is a subsequence of "ABCDE" while "AEC" is not).
Here is an example:
S = "rabbbit", T = "rabbit"
Return 3.
思路1
开始很容易想到深搜,通过flags数组做标记位,得到子串的个数
代码:
import java.util.Scanner; public class DistinctSubsequences { private static int disNum = 0; public static int numDistinct(String S, String T) { int[] flags = new int[S.length()]; int num = 0; dfs(num, flags, 0, 0, S, T); return disNum; } public static void dfs(int num, int[] flags, int indexS, int indexT, String S, String T) { if (num == T.length()) { disNum++; } else { for (int i = indexS; i < S.length(); i ++) { if (S.charAt(i) == T.charAt(indexT) && flags[i] == 0) { flags[i] = 1; num++; dfs(num, flags, i + 1, indexT + 1, S, T); flags[i] = 0; num--; } } } } public static void main(String[] args) { Scanner cin = new Scanner(System.in); while (cin.hasNext()) { String S = cin.nextLine(); String T = cin.nextLine(); disNum = 0; int res = numDistinct(S, T); System.out.println(res); } cin.close(); } }
但是在大集合的时候 Time Limit Exceeded
思路2
既然简单的深搜超时,只能考虑稍微复杂一点的DP了。可以参考动态规划经典的例子,最长公共子序列。
这里我采用二维数组int[][] dp来记录匹配子序列的个数,则状态方程为:
dp[0][0] = 1, T和S均为空串
dp[0][1..S.length() - 1] = 1, T为空串,S只有一种子序列匹配
dp[1..T.length() - 1][0] = 0, S为空串
dp[i][j] = dp[i][j - 1] + (T[i - 1] == S[j - 1] ? dp[i - 1][j - 1] : 0)
代码:
public class Solution { public static int numDistinct(String S, String T) { if (S == null || S.length() == 0) { return 0; } int[][] dp = new int[T.length() + 1][S.length() + 1]; dp[0][0] = 1; for (int i = 1; i <= S.length(); i++) { dp[0][i] = 1; } for (int i = 1; i <= T.length(); i++) { dp[i][0] = 0; } for (int i = 1; i <= T.length(); i++) { for (int j = 1; j <= S.length(); j++) { if (T.charAt(i - 1) == S.charAt(j - 1)) { dp[i][j] = dp[i][j - 1] + dp[i - 1][j - 1]; } else { dp[i][j] = dp[i][j - 1]; } } } return dp[T.length()][S.length()]; } }
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