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AiTechWorlds
AiTechWorlds
Visualize the O(n²) LIS dynamic programming table filling step-by-step, with synced multi-language code.
| 3 | 1 | 8 | 2 | 5 | 9 | 4 | 7 | |
|---|---|---|---|---|---|---|---|---|
| LIS | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
def lis(a):
n = len(a)
dp = [1] * n
for i in range(1, n):
for j in range(i):
if a[j] < a[i]:
dp[i] = max(dp[i], dp[j] + 1)
return max(dp)Longest Increasing Subsequence finds the longest subsequence whose elements are strictly increasing. The O(n²) DP sets dp[i] to the best length ending at index i.
| Time | O(n²) |
| Space | O(n) |
The Longest Increasing Subsequence (LIS) Visualizer animates the O(n²) dynamic programming solution. dp[i] holds the length of the longest increasing subsequence ending at index i, computed by checking all earlier elements smaller than a[i]. The answer is the maximum dp value. Time is O(n²) and space is O(n).
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Watch dp[i] update by comparing each earlier element a[j] < a[i].
Step through
Use Step Forward/Back or the timeline to follow each comparison.
Read the code
View the LIS 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.