Dynamic Programming 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.
Following are the most important Dynamic Programming problems asked in various Technical Interviews.
- Longest Common Subsequence
- Longest Increasing Subsequence
- Edit Distance
- Minimum Partition
- Ways to Cover a Distance
- Longest Path In Matrix
- Subset Sum Problem
- Optimal Strategy for a Game
- 0-1 Knapsack Problem
- Boolean Parenthesization Problem
- Shortest Common Supersequence
- Matrix Chain Multiplication
- Partition problem
- Rod Cutting
- Coin change problem
- Word Break Problem
- Maximal Product when Cutting Rope
- Dice Throw Problem
- Box Stacking
- Egg Dropping Puzzle
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