15 LeetCode Problems to Get Better at Dynamic Programming
Master the art of dynamic programming with these 15 curated LeetCode problems. Practice key concepts, hone your problem-solving skills, and get ready to ace your next coding interview!
Hello guys, Dynamic programming (DP) is a powerful technique used to solve complex problems by breaking them down into simpler subproblems but at the same time, its one of the tricky topic for interviews.
It’s really important to master DP for coding interviews, especially for tech giants like Google, Facebook, and Amazon.
Earlier, I have shared Coding interview guides and resources and In this guide, I'll share 15 LeetCode problems that are perfect for sharpening your DP skills.
Each problem in this list will push you to think about subproblems, memoization, and optimal substructure, and you'll tackle everything from classic "house robber" problems to complex matrix-based challenges.
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15 Dynamic Programming Problems for Coding Interviews
Whether you're new to DP or looking to hone your skills, these problems will help.
1. Climbing Stairs
Problem Description: You are climbing a staircase with n
steps. You can either take 1 step or 2 steps at a time. In how many distinct ways can you climb to the top?
LeetCode Link: Climbing Stairs
Tip: Think of it as a Fibonacci sequence where the number of ways to get to step n
is the sum of the ways to get to steps n-1
and n-2
.
2. House Robber
Problem Description: A robber is deciding which houses to rob tonight, but he cannot rob two adjacent houses. Find the maximum amount of money he can rob.
LeetCode Link: https://leetcode.com/problems/house-robber/
Tip: For each house, decide whether to rob it (and skip the adjacent one) or skip it. Use dynamic programming to store the optimal result for each house.
3. Longest Increasing Subsequence
Problem Description: Given an array of integers, find the length of the longest increasing subsequence.
LeetCode Link: Longest Increasing Subsequence
Tip: Use a DP array where each element at index i
stores the length of the longest increasing subsequence that ends at i
. Compare each element with all the previous elements to update the DP array.
4. Coin Change
Problem Description: Given an array of coin denominations and an amount, determine the fewest number of coins needed to make up that amount.
LeetCode Link: Coin Change
Tip: Think of this as a knapsack problem where you are trying to minimize the number of coins. Use a bottom-up DP approach to find the solution.
5. Partition Equal Subset Sum
Problem Description: Given a non-empty array, determine if the array can be partitioned into two subsets such that their sums are equal.
LeetCode Link: Partition Equal Subset Sum
Tip: This problem can be reduced to a 0/1 knapsack problem. Use a DP array where each index represents whether a subset with that sum is possible.
6. Unique Paths
Problem Description: You are given an m x n
grid. Your task is to count how many unique paths exist from the top-left corner to the bottom-right corner, only moving right or down.
LeetCode Link: Unique Paths
Tip: Use a DP table where each cell contains the number of paths to reach that cell. The value is the sum of the paths from the cell above and the cell to the left.
7. Edit Distance
Problem Description: Given two strings, find the minimum number of operations (insertions, deletions, or substitutions) required to convert one string into the other.
LeetCode Link: Edit Distance
Tip: Create a 2D DP table where dp[i][j]
represents the minimum operations needed to convert the first i
characters of one string to the first j
characters of the other string.
8. Minimum Path Sum
Problem Description: Given an m x n
grid filled with non-negative numbers, find a path from the top-left to the bottom-right which minimizes the sum of the numbers along the path.
LeetCode Link: Minimum Path Sum
Tip: Use a DP table where each cell contains the minimum path sum to reach that cell. Update the value by considering the cell above and the cell to the left.
9. Word Break
Problem Description: Given a string and a dictionary of words, determine if the string can be segmented into a space-separated sequence of dictionary words.
LeetCode Link: Word Break
Tip: Use a DP array where each index represents whether the substring up to that index can be segmented. Update it by checking all substrings and whether they are in the dictionary.
10. Palindromic Substrings
Problem Description: Given a string, count how many palindromic substrings exist.
LeetCode Link: Palindromic Substrings
Tip: Use a DP table to store whether a substring is a palindrome. Start with smaller substrings and expand outward to check larger ones.
11. Longest Palindromic Subsequence
Problem Description: Given a string, find the longest palindromic subsequence.
LeetCode Link: Longest Palindromic Subsequence
Tip: Use a DP table where each cell stores the length of the longest palindromic subsequence in a substring. Expand the substring size and check for matches at the two ends.
12. Decode Ways
Problem Description: Given a string of digits, determine the total number of ways to decode it into letters where 'A' = 1, 'B' = 2, ..., 'Z' = 26.
LeetCode Link: Decode Ways
Tip: Use a DP array where each index represents the number of ways to decode the substring up to that index. Consider both one- and two-digit combinations.
13. Burst Balloons
Problem Description: Given n
balloons, each balloon has a number on it. Burst the balloons in such an order that maximizes the coins you collect.
LeetCode Link: Burst Balloons
Tip: Use DP and memoization to store the maximum coins you can collect for each subarray of balloons.
14. Maximum Product Subarray
Problem Description: Given an integer array, find the contiguous subarray within an array which has the largest product.
LeetCode Link: Maximum Product Subarray
Tip: Keep track of both the maximum and minimum product ending at each index. A negative number can turn a large negative product into a large positive product.
15. Regular Expression Matching
Problem Description: Implement regular expression matching with support for '.'
and '*'
.
LeetCode Link: Regular Expression Matching
Tip: Use a DP table where each cell represents whether a substring matches the pattern up to that point. Handle *
and .
with special cases.
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Also here is a nice coding interview preparation cheetsheet you can use to guide your preparation
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Conclusion
That’s all guys. Dynamic programming is a powerful technique that can solve complex problems by breaking them into smaller subproblems. These 15 LeetCode problems will help you practice DP in various forms, ranging from simple to more advanced problems. With these problems, you’ll be able to sharpen your skills and ace your next interview!
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All the best with your coding interview prep.