Longest Common Subsequence

Problem

Given two strings a and b, return the length of their longest common subsequence (characters in the same relative order, not necessarily contiguous).

Constraints

• 1 ≤ a.length, b.length ≤ 1000
• lowercase English

Approach — Dynamic Programming

This is a Dynamic Programming problem. The idea: break the problem into overlapping subproblems and build the answer up, caching results so nothing is recomputed. Work through the reference code below line by line, then re-derive it yourself in the editor — that's how the pattern sticks.

Complexity: O(n) to O(n²) time.

Solution code

Python

class Solution:
    def longestCommonSubsequence(self, a, b):
        m, n = len(a), len(b)
        dp = [[0] * (n + 1) for _ in range(m + 1)]
        for i in range(1, m + 1):
            for j in range(1, n + 1):
                if a[i - 1] == b[j - 1]:
                    dp[i][j] = dp[i - 1][j - 1] + 1
                else:
                    dp[i][j] = max(dp[i - 1][j], dp[i][j - 1])
        return dp[m][n]

Java

class Solution {
    public int longestCommonSubsequence(String a, String b) {
        int m = a.length(), n = b.length();
        int[][] dp = new int[m + 1][n + 1];
        for (int i = 1; i <= m; i++) {
            for (int j = 1; j <= n; j++) {
                if (a.charAt(i - 1) == b.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 dp[m][n];
    }
}

Practice it

Reading a solution isn't the same as being able to write it under pressure. Open this problem in the in-browser editor, hide the solution, and solve it from scratch — your code runs against real test cases instantly.