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cs.SE2026

DRAGON: Robust Classification for Very Large Collections of Software Repositories

Stefano Balla, Stefano Zacchiroli, Thomas Degueule +2

The ability to automatically classify source code repositories with ''topics'' that reflect their content and purpose is very useful, especially when navigating or searching throug…

cs.SE2026

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…

cs.SE2026

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…

cs.SE2026

Package-Aware Approach for Repository-Level Code Completion in Pharo

Omar Abedelkader, Stéphane Ducasse, Oleksandr Zaitsev +2

Pharo offers a sophisticated completion engine based on semantic heuristics, which coordinates specific fetchers within a lazy architecture. These heuristics can be recomposed to s…

cs.SE2026

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…

cs.SE2025

Client--Library Compatibility Testing with API Interaction Snapshots

Gustave Monce, Thomas Degueule, Jean-Rémy Falleri +1

Modern software development heavily relies on third-party libraries to speed up development and enhance quality. As libraries evolve, they may break the tacit contract established…