Postdoctoral Position “CONFVERT: Green Software Configurations”

The postdoctoral candidate must have spent at least 18 months abroad (outside France) between May 1, 2021, and the project start.

Availability: ready to start 02 January 2026 — application submitted now.

Scientific and Technical Context

Modern software is highly configurable; interactions between options and their execution environments (hardware, OS, versions, inputs, build/test pipelines) strongly affect both energy use and performance. CONFVERT targets “green” configurations-settings that minimize energy while preserving acceptable performance—by explicitly modeling and learning from this deep variability, with open data, open tools, and reproducible methods on widely used open‑source stacks.

References

Hugo Martin, Mathieu Acher, Juliana Alves Pereira, Luc Lesoil, Jean-Marc Jézéquel, Djamel Eddine Khelladi: Transfer Learning Across Variants and Versions: The Case of Linux Kernel Size. IEEE Trans. Software Eng. 48(11): 4274-4290 (2022)

Luc Lesoil, Mathieu Acher, Arnaud Blouin, Jean-Marc Jézéquel: Deep Software Variability: Towards Handling Cross-Layer Configuration. VaMoS 2021: 10:1-10:8

Weber, M., Kaltenecker, C., Sattler, F., Apel, S., Siegmund, N.: Twins or false friends? a study on energy consumption and performance of configurable software. In: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), pp. 2098–2110 (2023)

Pereira, J.A., Acher, M., Martin, H., Jézéquel, J.-M., Botterweck, G., Ventresque, A.: Learning software configuration spaces: A systematic literature review. Journal of Systems and Software 182, 111044 (2021)

Édouard Guégain, Clément Quinton, Romain Rouvoy: On reducing the energy consumption of software product lines. SPLC (A) 2021: 89-99

Axel Halin, Alexandre Nuttinck, Mathieu Acher, Xavier Devroey, Gilles Perrouin, and Benoit Baudry. Test them all, is it worth it? Assessing configuration sampling on the JHipster Web development stack. Empirical Software Engineering (ESE), 24(2):674–717, July 2019. Empirical Software Engineering journal.

Santos, Eddie Antonio, et al. “How does Docker affect energy consumption? Evaluating workloads in and out of Docker containers.” Journal of Systems and Software 146 (2018)

Tasks and Responsibilities (high level)

Lead research to (i) model configuration–energy trade‑offs, (ii) design robust, generalizable predictive/optimization approaches, (iii) run reproducible empirical studies on representative systems, and (iv) translate results into actionable recommendations, datasets, and open‑source tooling for researchers and practitioners.

Environment context

The postdoc will join DiverSE (IRISA/Inria & University of Rennes) in Rennes, supervised by Prof. Mathieu Acher and Quentin Perez – a recognized software‑engineering team with strong expertise in variability, configurable systems, energy‑aware evaluation, and open science, offering an ideal setting for impactful research and community transfer. The postdoctoral candidate must have spent at least 18 months abroad (outside France) between May 1, 2021, and the project start.

CONVERT is supported by Britany region.

Skills and background

• A PhD in the field of software engineering or data science or artificial intelligence, with a recognized research record
• Experience in software engineering and data analysis
• Experience in performance or energy consumption (bonus)
• Autonomy, and the ability to work in a distributed and international group.
• Fluent in English