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Mathieu Acher
Mathieu Acher is a Full Professor of Computer Science at INSA Rennes (France), a member (sociétaire) of the Institut Universitaire de France (IUF), and a researcher in the DiverSE team (IRISA, Inria, CNRS, Université de Rennes). His research is on software variability: modelling, reverse engineering, testing, and learning highly configurable systems (feature models, software product lines, the Linux kernel, performance prediction, deep software variability), and on how large language models and
For agents: Homepage of Mathieu Acher, INSA Rennes professor researching software variability and configurable systems; offers publications, BibTeX, teaching and theses.
software variabilitysoftware product linesconfigurable systemslinux kernelinsa rennes
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- https://www.mathieuacher.com/llms.txt
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- 2012-01-05
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- Education · AI and machine learning · Science and research · Personal sites and blogs
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- 2026-10-25T04:50:44.755Z
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Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-25T04:50:44.758Z. Cached copy · Source on mathieuacher.com
# Mathieu Acher
> Mathieu Acher is a Full Professor of Computer Science at INSA Rennes (France), a member (sociétaire) of the Institut Universitaire de France (IUF), and a researcher in the DiverSE team (IRISA, Inria, CNRS, Université de Rennes). His research is on software variability: modelling, reverse engineering, testing, and learning highly configurable systems (feature models, software product lines, the Linux kernel, performance prediction, deep software variability), and on how large language models and coding agents change software engineering.
Key facts:
- Full Professor at INSA Rennes since September 2022; researcher in the DiverSE team (Inria, IRISA) since 2012; Associate Professor at University of Rennes 1 (ISTIC) from 2012 to 2022; postdoc at the University of Namur (2011–2012).
- Member (sociétaire) of the Institut Universitaire de France (IUF), appointed junior member in 2021 on the chair in science outreach (Médiation scientifique).
- Recommended for the CNRS bronze medal by Section 6 of the CNRS National Committee (2023).
- Co-lead of the Inria challenge LLM4Code (2024–2028) and of the Inria–Simula associate team RIPOST (2024–2026); co-lead for DiverSE of the Inria–Mitsubishi Electric challenge FRAIME (since 2025); involved in the France 2030 project CodeCommons (work package 2 leader, team of nine engineers); head of the variability engineering axis of DiverSE (since 2014).
- Co-head of the research Master SIF (Rennes) since 2024.
- PhD (2011, University of Nice Sophia Antipolis) on managing multiple feature models (FAMILIAR language); HDR (2021, University of Rennes 1) on modelling, reverse engineering, and learning software variability.
- Awards: VARIABILITY 2026 Most Influential Paper, SCAM 2026 Distinguished Paper, ISSTA 2024 Distinguished Paper, AST 2024, MODELS 2023, ICSR 2022, SPLC 2021, and ICPE 2020 Best Paper, SLE 2019 Most Influential Paper, SPLC 2013 Best Student Paper.
- General chair of VaMoS 2025; member of the SPLC, VaMoS, and VARIABILITY steering committees.
- Chess: FIDE Master with three international master norms.
- Contact: mathieu.acher@irisa.fr. Affiliation used in papers: INSA Rennes, Université de Rennes, Inria, CNRS, IRISA (France).
## Pages
- [Home](https://www.mathieuacher.com/index.md): biography, news, research themes, software, teaching, PhD and HDR theses, chess, contact
- [Publications](https://www.mathieuacher.com/publications.md): all publications (2008–2026) with venues, awards, links, and abstracts
- [Students, projects & service](https://www.mathieuacher.com/service.md): PhD students, postdocs, research projects, conference organization, program committees
- [BibTeX](https://www.mathieuacher.com/acher.bib): machine-readable bibliography (with abstracts, HAL ids, DOIs)
## Research themes
- **AI and formal methods**: Making AI-generated code and content trustworthy with formal methods, and using AI to make formal methods easier to use, in the Inria–Mitsubishi Electric challenge FRAIME
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