Advanced · Module 21 · Lesson 4 of 4
DP State Patterns: 1D/2D/Knapsack vs. Interval DP, Tree DP, and Bitmask DP
Design minimal DP states and transition order across all 8 canonical DP families: 1D/2D Grid, Subsequence, 0/1 & Unbounded Knapsack, Interval DP (len 1..N), Tree DP, and Bitmask DP.
By the end you can
- Map problem constraints and decision structures to the 8 canonical DP state families
- Order loops correctly for 0/1 Knapsack (capacities high-to-low) vs Unbounded Knapsack (capacities low-to-high) and Interval DP (by length len = 1..n)
- Formulate Bitmask DP (dp[mask][u]) for N <= 20 ordering/TSP problems and Tree DP for subtree aggregations
Builds on One-dimensional problems, Grids and strings, Knapsack and subsets, Bit Manipulation Tricks and Submask Enumeration.
01 · A question first
In 1D Space-Optimized Knapsack, reversing a single inner loop from `w = W down to weight` into `w = weight up to W` silently changes the problem from 0/1 Knapsack (each item once) to Unbounded Knapsack (infinite copies of each item)! Why does loop direction control item reuse?
Make a guess before you read on.
02 · The idea
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What's inside
- Intuitive Explanation & Real-World Analogy
- Core Concepts & Visual Walkthrough
- Pseudocode
- Multi-Language Implementations (C++, Java, Python)
- Time & Auxiliary Space Complexity Derivation
- Edge Cases & Common Beginner Mistakes
- Alternative Approaches (Brute Force vs. Optimal)
- Pattern Recognition Guide & Three-Stage Practice Plan
03 · Practice
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