5 articles
LC 1143 Longest Common Subsequence is the foundational sequence DP problem at every FAANG company. Master the 2D recurrence, space-optimize to O(n), and learn how to reconstruct the actual LCS — skills that transfer directly to Edit Distance, Shortest Common Supersequence, and Diff algorithms.
LC 72 Edit Distance (Levenshtein Distance) is the hard-level sequence DP benchmark at Google, Amazon, and Meta. Master the 3-operation recurrence, space-optimize to O(n), and understand how this algorithm powers spell-checkers, DNA alignment, and autocomplete systems.
LC 1092 Shortest Common Supersequence combines LCS computation with DP table reconstruction to produce the actual shortest string containing both inputs as subsequences. A hard-level 2D DP problem asked at Google and Amazon that demands both algorithm depth and reconstruction skill.
LC 97 Interleaving String asks whether s3 can be formed by interleaving s1 and s2 while preserving character order. The 2D DP table dp[i][j] checks whether s3[:i+j] can be formed from s1[:i] and s2[:j] — a classic Boolean 2D DP problem asked at Google and Amazon.
LC 10 Regular Expression Matching implements "." (any char) and "*" (zero or more of preceding) using 2D DP. It is a Hard-level problem and the most complex string DP asked at Google and Meta — the star (*) handling requires 3 separate cases that trip up even experienced candidates.