All Modules

Data Structures & Algorithms

The mathematical foundations of computation. Discover the algebra, combinatorics, and analysis that power efficient algorithms through 39 interactive demonstrations.

This is not interview prep — it's the deep mathematics behind why algorithms work: monoids, generating functions, information-theoretic bounds, and probabilistic analysis.

Algebraic Foundations of Data Structures

Discover the hidden algebraic structures in algorithms: monoids, semigroups, and how they power segment trees and parallel computation

4 demos

Combinatorics of Trees

Explore Catalan numbers, generating functions, and the surprising connections between binary trees, Dyck paths, and parenthesizations

4 demos

Recurrences & Master Theorem

Master the analysis of divide-and-conquer algorithms through recursion trees, the Master Theorem, and geometric series

5 demos

Information-Theoretic Bounds

Understand fundamental limits: decision trees, entropy, and why comparison-based sorting requires Omega(n log n) comparisons

4 demos

Probabilistic Data Structures

Explore skip lists, Bloom filters, and HyperLogLog—structures that trade exactness for remarkable efficiency using probability

5 demos

Amortized Analysis

Learn to analyze sequences of operations using potential functions, proving that expensive operations are rare enough to be efficient

4 demos

Union-Find & Inverse Ackermann

Discover Union-Find with path compression and union by rank, achieving the almost-impossible O(α(n)) bound

4 demos

Fast Fourier Transform

Explore the most important algorithm in signal processing: how roots of unity enable O(n log n) polynomial multiplication

5 demos

Advanced Tree Structures

Study B-trees for disk optimization, persistent trees for version control, and van Emde Boas trees for integer keys

4 demos

Algorithms Playground & Quiz

Free exploration with all data structures, plus a comprehensive quiz testing your mathematical understanding

0 demos