Seeing Structure First
A reflection on eleven explorations in generic programming—how algorithms arise from algebraic structure.
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A reflection on eleven explorations in generic programming—how algorithms arise from algebraic structure.
18-part lecture series on efficient programming. Covers the intellectual foundations behind STL.
Collected notes on programming philosophy. Free PDF.
Blends discrete mathematics with analysis and algorithm design.
Rigorous foundations of generic programming. Connects algebra and algorithms. Stepanov’s magnum opus.
History of mathematical ideas underlying generic programming. More accessible than EoP.
Broad coverage of numerical algorithms in science and engineering. Classic cross-topic numerical algorithms.
Classic talk on recognizing algorithmic patterns. ‘No raw loops’ - shows how rotate solves many problems elegantly.
AlgoGraph brings functional programming elegance to graph algorithms with immutable data structures, pipe-based transformers, declarative selectors, and lazy views.
A C++17 header-only library implementing Computational Basis Transforms - a unified framework for understanding how FFT, logarithmic arithmetic, and Bayesian inference are all instances of the same pattern.
A collection of graduate problem set solutions in computational statistics, numerical methods, and algorithm design from my mathematics master's program.
The Miller-Rabin primality test demonstrates how probabilistic algorithms can achieve arbitrary certainty, trading absolute truth for practical efficiency.
The Russian peasant algorithm teaches us that one algorithm can compute products, powers, Fibonacci numbers, and more—once we see the underlying algebraic structure.
An exploration of Bloom filters as elegant probabilistic data structures that trade perfect recall for extraordinary space efficiency.