Learn how to solve the Longest Common Subsequence coding problem to prepare for your next technical interview! Longest Common Subsequence is a classic test of whether you can define a two-dimensional DP state and reason about choices across two inputs simultaneously. Get the state definition right and the solution writes itself. Get it wrong and you'll spin in circles.

Learn how to solve the Longest Increasing Subsequence coding problem to prepare for your next technical interview! Longest Increasing Subsequence sounds like a greedy problem. Just keep taking bigger numbers, right? That instinct fails fast. This problem exists to test whether you can slow down, recognize why greedy breaks, define state correctly, and build up a solution from first principles.

Learn how to solve the Word Break coding problem to prepare for your next technical interview! Interviewers love Word Break because it exposes whether you can translate a vague problem statement into a clean DP state definition. The algorithm itself isn't complicated. The hard part is seeing the problem the right way.

Learn how to solve the Unique Paths II coding problem to prepare for your next technical interview! Unique Paths II looks almost identical to Unique Paths. One small change: obstacles. That single twist forces you to slow down, re-examine every assumption, and adapt the same DP pattern carefully. Interviewers love this problem precisely because it separates candidates who understand the pattern from those who just memorized it.

Learn how to solve the Unique Paths coding problem to prepare for your next technical interview! Unique Paths tests whether you can recognize a counting dynamic programming pattern and model state correctly. It's a classic interview question because the logic scales cleanly to harder grid problems. Once you've internalized the thinking here, a whole family of harder problems opens up.

Learn how to solve the Target Sum coding problem to prepare for your next technical interview!

Learn how to solve the Coin Change coding problem to prepare for your next technical interview!

Learn how to solve the House Robber coding problem to prepare for your next technical interview!

Learn how to solve the Fibonacci Number coding problem to prepare for your next technical interview!

Learn how to solve the Climbing Stairs coding problem to prepare for your next technical interview!

Jump Game II is a classic follow-up to the original Jump Game problem. It’s not just about whether you can reach the end... now you have to do it in the fewest jumps possible! That small change turns a simple reachability problem into one that tests how well you can optimize greedy strategies or dynamic programming under pressure.

The "Jump Game" question is a popular one for interviews because it tests your ability to think greedily and work with dynamic movement through an array. It's a great warm-up for range-based greedy logic and helps build intuition for reachability problems, concepts that show up often in competitive coding and systems design.

Maximum Subarray - Kadane's Algorithm is is a classic problem that introduces one of the most elegant uses of dynamic programming. It teaches you how to keep track of optimal sub-solutions and make decisions based on current and previous results. Once you’ve got this down, it opens the door to more complex dynamic programming challenges.

Dynamic Programming (DP) is a powerful technique used to solve complex problems by breaking them down into simpler subproblems. Whether...