posted by organizer: xdevroey || 2489 views || tracked by 6 users: [display]

MASES 2018 : 1st International Workshop on Machine Learning and Software Engineering in Symbiosis


When Sep 3, 2018 - Sep 3, 2018
Where Montpellier, France
Submission Deadline Jun 25, 2018
Notification Due Jul 20, 2018
Final Version Due Jul 30, 2018
Categories    software engineering   machine learning

Call For Papers

The 1st International Workshop on Machine Learning and Software Engineering in Symbiosis will be held in Montpellier, France, September 3, 2018. It will be co-located with the 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE).

Twitter: #mases18


Major breakthroughs in Artificial Intelligence (AI) have raised strong interests from research and industry towards Machine Learning (ML), the discipline of AI that aims at building software that automatically learns from data. As a result, ML systems increasingly gain popularity and will soon proliferate in a broad range of domains. However, they also raise many questions, in particular regarding their reliable engineering. Conversely, recent advances in Software Engineering (SE) themselves rely on ML. Several software development activities can thus now benefit from AI-based assistance and we expect many more in the coming years.

This workshop aims at bringing together the SE and ML communities to reflect on the potential symbioses between their respective disciplines. As such, it targets innovative ML applications that improve SE practices, as well as new engineering methods for ML-based systems.


Topics include, but are not limited to:

- Machine learning for software engineering
- Applications of machine learning to software analysis, verification and validation,
- Naturalness-based code analysis,
- Analysis of software repositories,
- Human-machine collaboration for engineering software systems,
- Performance prediction of software systems,
- Natural language processing for requirements extraction.
- Engineering methods for machine-learning systems
- Automated machine learning,
- Scalable infrastructure for machine learning,
- Validation and verification of learning systems,
- Requirements engineering for machine-learning systems,
- Design of safety-critical learning software,
- Integration of learning systems in software ecosystems.

We invite original papers from 2 to 10 pages in the conference format (two columns IEEE conference publication format, title in 24pt font and full text in 10pt font, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf option) describing positions and visions as well as technical contributions and experience reports. Reports on existing research projects (e.g., H2020) and industrial perspectives are also welcome. Each contribution will be reviewed by at least three members of the programme committee.


Submission of full papers: June 15, 2018
Notification of acceptance: July 20, 2018
Camera Ready: July 30, 2018
Workshop date: September 3, 2018


Submissions will be handled via EasyChair:



Gilles Perrouin, PReCISE, NADI, University of Namur (Belgium)
Mathieu Acher, University of Rennes 1 / Inria Rennes (France)
Maxime Cordy, PReCISE, NADI, University of Namur / University of Luxembourg (Luxembourg)
Xavier Devroey, SERG, Delft University of Technology (The Netherlands)


Earl Barr, University College London (United Kingdom)
Jordi Cabot, Open University of Catalonia (Spain)
J¸rgen Cito, Massachusetts Institute of Technology (USA)
Jesse Davis, Katholieke Universiteit Leuven (Belgium)
RÈmi Emonet, Laboratoire Hubert Curien (France)
Robert Feldt, Blekinge Institute of Technology (Sweden)
BenoÓt Frenay, University of Namur (Belgium)
Elisa Fromont, University of Rennes 1 (France)
Patrick Heymans, University of Namur (Belgium)
Suman Jana, Columbia University (USA)
Marta Kwiatkowska University of Oxford (United Kingdom)
Yves Le Traon, University of Luxembourg (Luxembourg)
Karl Meinke, KTH Royal Institute of Technology (Sweden)
Tim Menzies, NC State University (USA)
Tien Nguyen, The University of Texas at Dallas (USA)
Fabio Palomba, University of Zurich (Switzerland)
Annibale Panichella, Delft University of Technology (The Netherlands)
Jean-Francois Raskin, UniversitÈ Libre de Bruxelles (Belgium)
Pierre-Yves Schobbens, University of Namur (Belgium)
Koushik Sen University of California, Berkley (USA)
Alison M. Smith, Decisive Analytics (USA)
Paolo Tonella, Fondazione Bruno Kessler (Italy)
Zhenchang Xing, Australian National University (Australia)
and the workshop organisers.

Related Resources

ICDM 2021   21th Industrial Conference on Data Mining
MLDM 2021   17th International Conference on Machine Learning and Data Mining
QuaInT 2021   Workshop on the Quantum Information Technologies
ITE 2021   2nd International Conference on Integrating Technology in Education
AICA 2020   O'Reilly AI Conference San Jose
SI-DAMLE 2020   Special Issue on Data Analytics and Machine Learning in Education
NLPCL 2021   2nd International Conference on Natural Language and Computational Linguistics
Fintech 2020   Sustainaility (Q2): Fintech: Recent Advancements in Modern Techniques, Methods and Real-World Solutions
SA-TTA 2021   The 9th track on Software Architecture: Theory, Technology, and Applications (SA-TTA) at the 36th ACM/SIGAPP Symposium On Applied Computing (SAC 2021)
SOFSEM 2021   47th International Conference on Current Trends in Theory and Practice of Computer Science