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            <namePart type="given">Pedro</namePart>
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    <abstract>The world’s 7,000+ languages vary widely in the availability of resources for natural language processing, motivating efforts to systematically categorize them by their degree of resourcefulness. A similar disparity exists among programming languages; however, no resource-tier taxonomy has been established for code. As large language models grow increasingly capable of generating code, such a taxonomy becomes essential. To fill this gap, we present the first reproducible programming-language resource classification, grouping 646 languages into four tiers. We show that only 1.9% of languages (Tier 3, High) account for 74.6% of all tokens in seven major web-derived corpora, while 71.7% of languages (Tier 0, Scarce) contribute just 1.0%. Statistical analyses of within-tier inequality, dispersion, and distributional skew confirm that this imbalance is both extreme and systematic. Our results provide a principled framework for dataset curation and tier-aware evaluation of multilingual large language models, as well as the first quantitative picture of code availability on the web.</abstract>
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%0 Conference Proceedings
%T A Taxonomy of Programming Languages for Code Generation
%A Raihan, Nishat
%A Newman, Christian
%A Zampieri, Marcos
%Y Ortiz Suarez, Pedro
%Y Burchell, Laurie
%Y Ljubešić, Nikola
%Y Scherrer, Yves
%Y Laippala, Veronika
%Y Dinić, Vuk
%Y Vaughan, Thom
%S Proceedings of the 13th Web-as-Corpus Workshop
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-481-1
%F raihan-etal-2026-taxonomy
%X The world’s 7,000+ languages vary widely in the availability of resources for natural language processing, motivating efforts to systematically categorize them by their degree of resourcefulness. A similar disparity exists among programming languages; however, no resource-tier taxonomy has been established for code. As large language models grow increasingly capable of generating code, such a taxonomy becomes essential. To fill this gap, we present the first reproducible programming-language resource classification, grouping 646 languages into four tiers. We show that only 1.9% of languages (Tier 3, High) account for 74.6% of all tokens in seven major web-derived corpora, while 71.7% of languages (Tier 0, Scarce) contribute just 1.0%. Statistical analyses of within-tier inequality, dispersion, and distributional skew confirm that this imbalance is both extreme and systematic. Our results provide a principled framework for dataset curation and tier-aware evaluation of multilingual large language models, as well as the first quantitative picture of code availability on the web.
%U https://aclanthology.org/2026.wac-1.4/
%P 37-52

Markdown (Informal)

[A Taxonomy of Programming Languages for Code Generation](https://aclanthology.org/2026.wac-1.4/) (Raihan et al., WAC 2026)

• A Taxonomy of Programming Languages for Code Generation (Raihan et al., WAC 2026)

ACL

• Nishat Raihan, Christian Newman, and Marcos Zampieri. 2026. A Taxonomy of Programming Languages for Code Generation. In Proceedings of the 13th Web-as-Corpus Workshop, pages 37–52, Budapest, Hungary. Association for Computational Linguistics.