Dynamic Programming Questions

Solving problems with overlapping subproblems and optimal substructure by memoization (top-down) and tabulation (bottom-up). Covers recognizing DP-amenable problems, defining state, transition and base cases, 1D and 2D sequence and grid formulations (knapsack and its variants, coin change, LIS, LCS, edit distance, sequence alignment, regular-expression and wildcard matching, counting-ways problems), interval DP (matrix chain, palindrome partitioning), space optimization with rolling arrays, solution reconstruction, longest paths in a DAG, game and expected-value DP, bitmask and tree DP, speeding up a DP (monotone queue, convex hull trick, divide-and-conquer optimization, bitsets, meet in the middle), and judging greedy versus DP. Ground covered elsewhere: probabilistic model inference, production caching and debugging practice, and general graph shortest-path algorithms.