30 Dynamic Programming LeetCode Problems You Must Know [2026]

The most frequently asked DP problems at FAANG companies: Coin Change (LC 322), Longest Common Subsequence (LC 1143), Edit Distance (LC 72), Partition Equal Subset Sum (LC 416), Word Break (LC 139), Best Time to Buy and Sell Stock III (LC 123), Burst Balloons (LC 312), and Longest Increasing Subsequence (LC 300). Google asks Edit Distance and Burst Balloons particularly often.

Start with Fibonacci and Climbing Stairs to understand memoization. Then do House Robber (skip-or-take pattern). Then Coin Change (unbounded knapsack). Then Longest Common Subsequence (2D DP). In that order, each problem builds on the previous. Do not start with hard problems — the pattern clarity in easy and medium problems is what builds the intuition.

The 0/1 knapsack problem is: given items with weights and values, pick items to maximize value without exceeding a weight limit, where each item can be used at most once. It is the archetype for a large class of interview DP problems. Partition Equal Subset Sum, Target Sum, and Last Stone Weight II are all disguised knapsack problems. Once you recognize the knapsack template, these "hard" problems become routine.

DP time complexity is typically O(n × m) where n and m are the dimensions of the state space. For 1D DP problems: O(n) time and O(n) space, often reducible to O(1) space. For 2D DP (like LCS or Edit Distance): O(n × m) time and space, often reducible to O(min(n,m)) space with a rolling array.