A
AiTechWorlds
AiTechWorlds
Visualize the LCS 2D DP table comparing two strings character by character, with synced multi-language code.
| — | G | A | C | |
|---|---|---|---|---|
| — | 0 | 0 | 0 | 0 |
| A | 0 | 0 | 0 | 0 |
| G | 0 | 0 | 0 | 0 |
| C | 0 | 0 | 0 | 0 |
| A | 0 | 0 | 0 | 0 |
| T | 0 | 0 | 0 | 0 |
def lcs(a, b):
n, m = len(a), len(b)
dp = [[0]*(m+1) for _ in range(n+1)]
for i in range(1, n+1):
for j in range(1, m+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[n][m]Longest Common Subsequence finds the longest sequence appearing in both strings in order (not necessarily contiguous), filling a 2D table by comparing characters.
| Time | O(n × m) |
| Space | O(n × m) |
The Longest Common Subsequence (LCS) Visualizer animates the 2D dynamic programming solution that finds the longest sequence appearing in both strings in order. When characters match, dp[i][j] = dp[i-1][j-1] + 1; otherwise it is the max of the cell above or to the left. It runs in O(n × m) time and space.
Press Play
Watch the table fill as the two strings are compared character by character.
Step through
Use Step Forward/Back or the timeline to follow each match/mismatch decision.
Read the code
View the LCS DP in C++, Java, Python, or JavaScript and copy it.
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Last reviewed on June 14, 2026 by the AiTechWorlds Tools Team. All processing runs locally in your browser.