Characterizing the Adoption of Autonomous Coding Agents in Functional Programming Repositories
Resumo
Autonomous coding agents are increasingly participating in collaborative software development, yet little is known about their adoption in functional programming ecosystems. This paper presents an empirical study on the adoption of autonomous coding agents in GitHub repositories developed with functional programming languages. We analyzed 35 repositories written in Elixir, Haskell, F#, Erlang and OCaml, comprising 158 AI-generated Pull Requests. The results show that AI-generated contributions are already present in mature and actively maintained functional programming repositories. Most Pull Requests are small and incremental. OpenAI Codex accounts for 78 of the 93 AI-generated Pull Requests in Elixir repositories, whereas GitHub Copilot is responsible for 38 of the 39 Pull Requests identified in F# repositories. Elixir also presents the highest Pull Request acceptance rate (77.4%), while repository popularity exhibits no meaningful association with AI-generated Pull Request activity (𝜌 = −0.029 for stars and 𝜌 = −0.038 for forks).
Palavras-chave:
Autonomous Coding Agents, Functional Programming, Software Engineering, Mining Software Repositories, GitHub, Empirical Study
Referências
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Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021. Evaluating Large Language Models Trained on Code. CoRR abs/2107.03374 (2021). DOI: 10.48550/arXiv.2107.03374
Taher A. Ghaleb. 2026. Fingerprinting AI Coding Agents on GitHub. In Proceedings of the 23rd International Conference on Mining Software Repositories (MSR ’26). ACM. DOI: 10.1145/3793302.3793582
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Ahmed E. Hassan, Gustavo Ansaldi Oliva, Dayi Lin, Boyuan Chen, and Zhen Ming Jiang. 2024. Towards AI-Native Software Engineering (SE) 3.0: A Vision and a Challenge Roadmap. CoRR abs/2410.06107 (2024). DOI: 10.48550/arXiv.2410.06107
Hao Li, Haoxiang Zhang, and Ahmed E. Hassan. 2025. The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering. CoRR abs/2507.15003 (2025). DOI: 10.48550/arXiv.2507.15003
Daniel Ogenrwot and John Businge. 2026. How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests. In Proceedings of the 23rd International Conference on Mining Software Repositories (MSR ’26). ACM, 924–928. DOI: 10.1145/3793302.3793603
Romain Robbes, Théo Matricon, Thomas Degueule, André C. Hora, and Stefano Zacchiroli. 2026. Agentic Much? Adoption of Coding Agents on GitHub. ACM Transactions on Software Engineering and Methodology (2026). DOI: 10.1145/3822180
Margaret-Anne D. Storey, Alexey Zagalsky, Fernando Marques Figueira Filho, Leif Singer, and Daniel M. Germán. 2017. How Social and Communication Channels Shape and Challenge a Participatory Culture in Software Development. IEEE Transactions on Software Engineering 43, 2 (2017), 185–204. DOI: 10.1109/TSE.2016.2584053
Simon Thompson. 2011. Haskell: The Craft of Functional Programming (3 ed.). Addison-Wesley.
TIOBE Software. 2026. TIOBE Programming Community Index. [link]. Accessed: 2026-07-08.
Miku Watanabe, Hao Li, Yutaro Kashiwa, Brittany Reid, Hajimu Iida, and Ahmed E. Hassan. 2026. On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub. ACM Transactions on Software Engineering and Methodology (2026). DOI: 10.1145/3798166
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021. Evaluating Large Language Models Trained on Code. CoRR abs/2107.03374 (2021). DOI: 10.48550/arXiv.2107.03374
Taher A. Ghaleb. 2026. Fingerprinting AI Coding Agents on GitHub. In Proceedings of the 23rd International Conference on Mining Software Repositories (MSR ’26). ACM. DOI: 10.1145/3793302.3793582
GitHub. 2026. GitHub REST API Documentation. [link]. Accessed: 2026-07-08.
Georgios Gousios, Martin Pinzger, and Arie van Deursen. 2014. An Exploratory Study of the Pull-Based Software Development Model. In Proceedings of the 36th International Conference on Software Engineering (ICSE 2014). ACM, 345–355. DOI: 10.1145/2568225.2568260
Ahmed E. Hassan, Gustavo Ansaldi Oliva, Dayi Lin, Boyuan Chen, and Zhen Ming Jiang. 2024. Towards AI-Native Software Engineering (SE) 3.0: A Vision and a Challenge Roadmap. CoRR abs/2410.06107 (2024). DOI: 10.48550/arXiv.2410.06107
Hao Li, Haoxiang Zhang, and Ahmed E. Hassan. 2025. The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering. CoRR abs/2507.15003 (2025). DOI: 10.48550/arXiv.2507.15003
Daniel Ogenrwot and John Businge. 2026. How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests. In Proceedings of the 23rd International Conference on Mining Software Repositories (MSR ’26). ACM, 924–928. DOI: 10.1145/3793302.3793603
Romain Robbes, Théo Matricon, Thomas Degueule, André C. Hora, and Stefano Zacchiroli. 2026. Agentic Much? Adoption of Coding Agents on GitHub. ACM Transactions on Software Engineering and Methodology (2026). DOI: 10.1145/3822180
Margaret-Anne D. Storey, Alexey Zagalsky, Fernando Marques Figueira Filho, Leif Singer, and Daniel M. Germán. 2017. How Social and Communication Channels Shape and Challenge a Participatory Culture in Software Development. IEEE Transactions on Software Engineering 43, 2 (2017), 185–204. DOI: 10.1109/TSE.2016.2584053
Simon Thompson. 2011. Haskell: The Craft of Functional Programming (3 ed.). Addison-Wesley.
TIOBE Software. 2026. TIOBE Programming Community Index. [link]. Accessed: 2026-07-08.
Miku Watanabe, Hao Li, Yutaro Kashiwa, Brittany Reid, Hajimu Iida, and Ahmed E. Hassan. 2026. On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub. ACM Transactions on Software Engineering and Methodology (2026). DOI: 10.1145/3798166
Publicado
08/09/2026
Como Citar
MENDES, Kayre; COELHO, Jailton.
Characterizing the Adoption of Autonomous Coding Agents in Functional Programming Repositories. In: WORKSHOP EM ENGENHARIA DE SOFTWARE PARA PROGRAMAÇÃO FUNCIONAL (SE4FP), 2. , 2026, São Paulo/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 25-29.
DOI: https://doi.org/10.5753/se4fp.2026.32864.
