Longest Common Subsequence (LCS) Visualizer
Why do we add
+1 in LCS DP when characters match?
When characters don't match in LCS, why take
max(dp[i-1][j], dp[i][j-1])?
What is the time complexity of the standard Dynamic Programming approach for LCS of two strings of lengths n and m?
What does a tie in the DP table (e.g., dp[i-1][j] == dp[i][j-1]) imply?
If two strings X and Y are identical (X = Y), what is the LCS?
For very large inputs, what is the biggest limitation in standard O(n*m) DP?
What is the main trade-off of the Rolling Array optimization for LCS?
Which statement is true for X='ABCBDAB', Y='BDCABA'?
Can the LCS length be greater than the length of the shorter string?
What is the space complexity of Rod Cutting with DP (Bottom-Up)?