DDSA Solutions

Dynamic Programming

133 problems · 86 with full explanations

7 Easy59 Medium18 Hard
Dynamic programming solves problems by breaking them into overlapping sub-problems and storing results to avoid redundant work. The key steps are: define state, write a recurrence relation, set base cases, and choose top-down (memoization) or bottom-up (tabulation). DP often yields O(n²) → O(n) time improvements over brute force.

How to practice

To practice Dynamic Programming problems effectively, start with the Easy problems listed below, trace through each solution on paper, then re-implement without looking. When you can recognise the dynamic programming pattern within 30 seconds of reading a new problem, move on to Medium difficulty. Use the related topic pages and our study guide for a structured progression.

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Start here (Easy + explained)

All Dynamic Programming problems