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Every Named Algorithm

A CodeSights flagship for the computing crowd: 745 named algorithms of computer science with the columns nobody ships flat, worst and average time complexity and space complexity exactly as {{Infobox algorithm}} states them (O(n log n) stays a string, because pretending it is a number would be false precision), inventors and publication years from prose, field across ten areas from sorting to computational geometry, and paradigm (divide and conquer, greedy, dynamic programming...) tagged only when the article uses the words. The timeline is computing's own: merge sort opens the era in 1945 from von Neumann's EDVAC work, Dijkstra conceives his shortest path in 1956, Hoare's quicksort lands in 1959, and the golden age is the 1970s through 1990s by test. RSA carries 1973 rather than the famous 1977, because Clifford Cocks invented it in secret at GCHQ first, and the same article taught the field matcher humility: a GCHQ history being "classified" is not a machine learning classifier. The extraction gauntlet also included nationality adjectives posing as inventors (quicksort was briefly invented by "British") and citation templates leaking their arguments into complexity strings until the cleaner learned to peel nested templates whole. Complexity strings are markup-free by test, Big-O notation appears in over 70 percent of worst-case entries, field and paradigm vocabularies are closed sets, and anchors pin Quicksort, Dijkstra, merge sort and RSA. Twelve acceptance tests.
745 rows 1 file last pulled 2026-10-13
Algorithms 745 rows × 11 columns
AlgorithmAlgorithm_IDFieldParadigmYear_PublishedInventorsTime_Complexity_WorstTime_Complexity_AverageSpace_ComplexityData_StructureAlgorithm_URL

Questions and answers

What is the Every Named Algorithm dataset?

A CodeSights flagship for the computing crowd: 745 named algorithms of computer science with the columns nobody ships flat, worst and average time complexity and space complexity exactly as {{Infobox algorithm}} states them (O(n log n) stays a string, because pretending it is a number would be false precision), inventors and publication years from prose, field across ten areas from sorting to computational geometry, and paradigm (divide and conquer, greedy, dynamic programming...) tagged only when the article uses the words. The timeline is computing's own: merge sort opens the era in 1945 from von Neumann's EDVAC work, Dijkstra conceives his shortest path in 1956, Hoare's quicksort lands in 1959, and the golden age is the 1970s through 1990s by test. RSA carries 1973 rather than the famous 1977, because Clifford Cocks invented it in secret at GCHQ first, and the same article taught the field matcher humility: a GCHQ history being "classified" is not a machine learning classifier. The extraction gauntlet also included nationality adjectives posing as inventors (quicksort was briefly invented by "British") and citation templates leaking their arguments into complexity strings until the cleaner learned to peel nested templates whole. Complexity strings are markup-free by test, Big-O notation appears in over 70 percent of worst-case entries, field and paradigm vocabularies are closed sets, and anchors pin Quicksort, Dijkstra, merge sort and RSA. Twelve acceptance tests.

How big is the Every Named Algorithm dataset?

745 rows in one CSV file, with 11 columns in total: Algorithm, Algorithm_ID, Field, Paradigm, Year_Published, Inventors, Time_Complexity_Worst, Time_Complexity_Average, Space_Complexity, Data_Structure, Algorithm_URL.

Where does the data come from?

It is built by programmatically scraping en.wikipedia.org, last pulled on 2026-10-13. Datasets are versioned; older versions stay downloadable.

Is the dataset free to download?

Yes. Every CodeSights dataset is completely free as a CSV download; a free account is all it takes. Anyone can preview the data without signing in.

Can I see the code that built this dataset?

Yes. The exact Python scraper that built it is viewable on the dataset page by any signed-in member, so every number is reproducible.

Can the data contain errors?

Automated scraping leaves room for error and the underlying sources change over time, so no version is guaranteed accurate or complete. If a number matters, verify it against the original source.

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