2 citations · 2 across the 8 of their papers we have counts for
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"We Permit the Use of AI, but [...]": The Landscape of AI Policies in Popular Open Source Projects
Andre Hora, Romain Robbes, Stefano Zacchiroli
Open source communities are converging on a new governance artifact: the AI contribution policy. These policies barely existed a few months ago and are now being written and adopte…
TestMiner: Software Testing Analysis for GitHub Repositories
Andre Hora, José Miguel Rojas, Romain Robbes
Software systems have unique testing characteristics. Some projects can emphasize unit tests, while others may focus on end-to-end testing. Test organization may vary across ecosys…
Agentic Very Much! Adoption of Coding Agent in New GitHub Projects
Romain Robbes, Théo Matricon, Thomas Degueule +2
In previous work, we investigated the adoption of coding agents in GitHub projects, finding that it was very significant. This study follows this line of work, but analyses new pro…
AI Policy, Disclosure, and Human in the Loop: How Are Contribution Guidelines Adapting to GenAI?
Andre Hora, Romain Robbes
Generative AI (GenAI) has recently transformed software development. Due to the ease of generating code, open source projects are experiencing a growth in contributions. To address…
What's Inside a GitHub Repository? An Empirical Study on the Contents of 10K Projects
Andre Hora, João Eduardo Montandon, Diego Elias Costa
GitHub is the largest code hosting platform, with millions of repositories spanning multiple technologies. Despite this, little is known about the actual contents of GitHub's repos…
Are Coding Agents Generating Over-Mocked Tests? An Empirical Study
Andre Hora, Romain Robbes
Coding agents have received significant adoption in software development recently. Unlike traditional LLM-based code completion tools, coding agents work with autonomy (e.g., invok…
Promises, Perils, and (Timely) Heuristics for Mining Coding Agent Activity
Romain Robbes, Théo Matricon, Thomas Degueule +2
In 2025, coding agents have seen a very rapid adoption. Coding agents leverage Large Language Models (LLMs) in ways that are markedly different from LLM-based code completion, maki…
Agentic Much? Adoption of Coding Agents on GitHub
Romain Robbes, Théo Matricon, Thomas Degueule +2
In the first half of 2025, coding agents have emerged as a category of development tools that have very quickly transitioned to the practice. Unlike ''traditional'' code completion…