Break down complex DP problems into simple, visual steps. Watch how optimal subproblems build up to solve bigger challenges, making DP intuitive and approachable.
Visualize how a robot finds all possible unique paths from top-left to bottom-right corner of a grid, moving only right or down.
Longest Common Subsequence visualization
0/1 Knapsack Problem visualization
Like many CS students, I found myself diving deep into LeetCode while preparing for technical interviews. Dynamic Programming was always the topic that made me pause and scratch my head. The concept of breaking down complex problems into simpler ones made sense in theory, but applying it felt like solving a puzzle in the dark.
Everything changed when I started visualizing these problems. Drawing out the process step by step, seeing how optimal solutions were built from smaller pieces, watching patterns emerge from seemingly chaotic problems—suddenly, DP started to click. What once looked like intimidating algorithms transformed into elegant solutions that I could understand and appreciate.
This journey from confusion to clarity inspired me to create DP Visualizer. As a student at the University of Georgia, I wanted to transform my "aha!" moment into a tool that could help others experience that same breakthrough. By turning abstract concepts into interactive visualizations, I hope to make Dynamic Programming more approachable and maybe even enjoyable for others walking the same path.
What you see here is just the beginning. There are so many fascinating DP problems to visualize, patterns to uncover, and concepts to explore together. Whether you're preparing for interviews, studying algorithms, or simply curious about DP, I hope these visualizations help illuminate your path as they did mine.
Let's make Dynamic Programming less daunting, one visualization at a time.