5 Dynamic Programming Patterns You Must Know
Dynamic programming is often considered the hardest topic in coding interviews. However, by mastering these 5 core patterns, you can solve 80% of DP problems with confidence.
Pattern 1: Fibonacci Style
Problems where the current state depends on previous states in a simple way.
Example: Climbing Stairs, House Robber
Pattern 2: 0/1 Knapsack
Choose or don't choose decisions with constraints.
Example: Subset Sum, Partition Equal Subset Sum
Pattern 3: Unbounded Knapsack
Similar to 0/1 Knapsack but items can be used multiple times.
Example: Coin Change, Rod Cutting
Pattern 4: Longest Common Subsequence
Two-sequence DP problems.
Example: Edit Distance, Longest Common Subsequence
Pattern 5: Palindrome Subsequence
String DP where we check substring properties.
Example: Longest Palindromic Substring, Palindrome Partitioning
Key Strategy
- Identify the pattern
- Define the DP state
- Write the recurrence relation
- Implement with memoization or tabulation
Master these patterns and DP interviews will become much easier!