Why is DP usually better than plain recursion?

Updated Apr 28, 2026

Short answer

It reduces time complexity from exponential to polynomial by eliminating redundant work.

Deep explanation

Dynamic Programming (DP) is an algorithmic paradigm that solves a given complex problem by breaking it into subproblems and stores the results of subproblems to avoid computing the same results again. It reduces time complexity from exponential to polynomial by eliminating redundant work.

Real-world example

Cashiers giving change using the minimum number of coins.

Common mistakes

  • Creating a memoization table but forgetting to check it before recursing.

Follow-up questions

  • What is the space complexity of this Fibonacci approach?

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