2 citations · 2 across the 2 of their papers we have counts for
5 papers
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…
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…
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…
Efficiently Ranking Software Variants with Minimal Benchmarks
Théo Matricon, Mathieu Acher, Helge Spieker +1
Benchmarking is a common practice in software engineering to assess the qualities and performance of software variants, coming from multiple competing systems or from configuration…
Prompting for Performance: Exploring LLMs for Configuring Software
Helge Spieker, Théo Matricon, Nassim Belmecheri +7
Software systems usually provide numerous configuration options that can affect performance metrics such as execution time, memory usage, binary size, or bitrate. On the one hand,…