An interactive, single-page visualizer covering three Algorithms II topics, built for a university midterm with step-by-step animation and pseudocode highlighting.
For an Algorithms II midterm, I kept noticing that algorithms like matrix chain multiplication are easy enough to code but hard to actually build real intuition for just by reading the code. You can trace through a DP table on paper once and still not really feel why it works.
Built three fully animated visualizations (Matrix Chain Multiplication using dynamic programming, Parallel Merge Sort using a fork-join model, and the Extended Euclidean Algorithm), each with step-by-step playback and pseudocode highlighting.
Rendered every visualization natively in SVG, including DP cost/split tables, recursion trees, and a Gantt chart of processor utilization, with no canvas API or external charting library.
Computed a live Brent's theorem bound (T_p ≤ W/p + D) alongside the Gantt chart to show the parallel merge sort's theoretical vs. visualized speedup.
Shipped as a single self-contained HTML file with no build step or dependencies, with dark/light theming persisted via localStorage.