Reading Algorithms Like an Engineer: What DiskANN Taught Me About Pseudocode

The first time I implemented Vamana from the DiskANN paper, my approximate nearest neighbor index was slower than brute force. On tiny test fixtures, brute force took 0.27 ms per query. My Vamana implementation took 22.98 ms. That sounds absurd. ANN exists to skip work. The problem was not the algorithm. It was how I mapped the paper's abstractions to actual data structures. A set is not a data structure The DiskANN pseudocode talks about sets L , V , and Nout(p) . That is fine for explanation.