LCS Visualizer

String A:

String B:

DP Table Visualization

Progress: 0 / 00%

		A	E	B	D	F

Speed:

500ms

Current Step Explanation:

Legend:

Current cell

Comparing cells

Character match

Traceback path

Pseudo Code:

function LCS(string A, string B):

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])

// After filling table, traceback to find LCS

Algorithm Overview

The Longest Common Subsequence (LCS) problem finds the longest subsequence common to two sequences. Unlike substrings, subsequences don't need to be consecutive elements.

For example, the LCS of "ABCDEF" and "AEBDF" is "ABDF" with length 4.

Legend:

Current cell

Comparing cells

Character match

Traceback path