Rebuilding the spellchecker, pt.4: Introduction to suggest algorithm

This page summarizes the projects mentioned and recommended in the original post on

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  • JamSpell

    Modern spell checking library - accurate, fast, multi-language

    There is, for example, a curious evaluation table provided by a modern ML-based spellchecker JamSpell. According to it, JamSpell is awesome—while Hunspell is a mere 0.03% better than dummy ("fix nothing") spellchecker... Which doesn't ring true, somehow!

  • hunspell

    The most popular spellchecking library.

    Those questions are open ones—and even the way they can be answered is unclear. Intuitively, Hunspell's suggestions are quite decent—otherwise, it wouldn't be the most widespread spellchecker, after all. A fair amount of "unhappy customers" can be easily found, too, in hunspell's repo issues. At the same time, one should distinguish between different reasons for the sub-par suggestion quality. It might be due to the algorithm itself, or due to the source data quality: the literal absence of the desired suggestion in the dictionary, or lack of aff-file settings that could've guided Hunspell to finding it.

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    Write Clean C++ Code. Always.. Sonar helps you commit clean C++ code every time. With over 550 unique rules to find C++ bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.

  • SymSpell

    SymSpell: 1 million times faster spelling correction & fuzzy search through Symmetric Delete spelling correction algorithm

    Some of the modern approaches to spellchecking still take this road: for example, SymSpell algorithm (claiming to be "1 million times faster") is at its core just a brilliant idea for a novel storage format for a flat word list, that allows optimizing the calculation of edit distance significantly.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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