Minimum Path Sum: A Dynamic Programming Walkthrough
Minimum Path Sum is a dynamic programming problem interviewers use early in a loop because it's a clean test of fundamentals. Can you define a DP state that's actually self-contained? Can you identify the transitions without overthinking? Candidates who haven't internalized how to walk through a 2D DP table will fumble the indexing, miss the base cases, or jump straight to in-place optimization without justifying it. The interviewer is watching for clean reasoning, not clever
20 hours ago10 min read
Russian Doll Envelopes: A Dynamic Programming Interview Walkthrough
Russian Doll Envelopes is a dynamic programming problem that interviewers love because it tests whether you can recognize a familiar problem hiding inside an unfamiliar one. The challenge is in realizing that with the right sort, the second dimension collapses into a classic Longest Increasing Subsequence problem. That recognition is the actual signal the interviewer is looking for.
4 days ago10 min read
Burst Balloons: A Dynamic Programming Interview Walkthrough
Interviewers reach for the Burst Balloons dynamic programming problem because it tests a specific mental move: when forward reasoning fails, can you flip the question and reason backward? Candidates pass when they can make that flip and then define a clean interval state; candidates who can't do that tend to spiral.
May 812 min read
Decode Ways: A Step-by-Step Dynamic Programming Interview Walkthrough
Interviewers reach for the Decode Ways dynamic programming problem when they want to see whether you can reason about validity, not just optimization. The recurrence itself is short, but every transition has a precondition, and a candidate who forgets to check those preconditions will count nonsense and not realize it. That's the actual test: can you define a state cleanly, validate every transition into it, and handle the boundary cases that break naive solutions?
May 29 min read
Edit Distance: A Step-by-Step Dynamic Programming Interview Walkthrough
Edit Distance is one of the cleanest tests an interviewer has for whether you can reason about multi-dimensional state and justify transitions from first principles, rather than pattern-match to a memorized template. The technique you build here - defining state over prefixes and anchoring decisions at a boundary - is the same one that unlocks Longest Common Subsequence, Regular Expression Matching, and most other two-string DP problems you'll encounter.
Apr 2710 min read
