Product lines can jeopardize their trade secrets, Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, pp.930-933, 2015. ,
DOI : 10.1109/SPLINE.2007.23
URL : https://hal.archives-ouvertes.fr/hal-01234342
FAMILIAR: A domain-specific language for large scale management of feature models, Science of Computer Programming, vol.78, issue.6, pp.657-681, 2013. ,
DOI : 10.1016/j.scico.2012.12.004
URL : https://hal.archives-ouvertes.fr/hal-00767175
Automated analysis of feature models 20 years later: A literature review, Information Systems, vol.35, issue.6, pp.615-708, 2010. ,
DOI : 10.1016/j.is.2010.01.001
Modeling and Building Software Product Lines with pure::variants, In SPLC Workshops, vol.296, 2010. ,
DOI : 10.1109/splc.2008.53
Variability-aware performance prediction: A statistical learning approach, 2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2013. ,
DOI : 10.1109/ASE.2013.6693089
On lazy and eager interactive reconfiguration In The Eighth International Workshop on Variability Modelling of Software-intensive Systems, VaMoS '14, pp.1-8, 2014. ,
FeatureIDE: A tool framework for feature-oriented software development, 2009 IEEE 31st International Conference on Software Engineering, pp.611-614, 2009. ,
DOI : 10.1109/ICSE.2009.5070568
The Anatomy of a Sales Configurator: An Empirical Study of 111 Cases, CAiSE'13, 2013. ,
Systems and software product line engineering with BigLever software gears, SPLC 2012 ,
Classification and regression trees, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol.44, issue.2, pp.14-23, 2011. ,
DOI : 10.2307/2531894
Variability Management and Assessment for User Interface Design, pp.81-106, 2017. ,
DOI : 10.1109/5.949485
Cost-Efficient Sampling for Performance Prediction of Configurable Systems (T), 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2015. ,
DOI : 10.1109/ASE.2015.45
Scalable prediction of non-functional properties in software product lines: Footprint and memory consumption, Information and Software Technology, vol.55, issue.3, 2013. ,
DOI : 10.1016/j.infsof.2012.07.020
Learning Contextual-Variability Models, IEEE Software, vol.34, issue.6, 2017. ,
DOI : 10.1109/MS.2017.4121211
URL : https://hal.archives-ouvertes.fr/hal-01659137
Learning-Based Performance Specialization of Configurable Systems, Inria Rennes ; University of Rennes, vol.1, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01467299
Using machine learning to infer constraints for product lines, Proceedings of the 20th International Systems and Software Product Line Conference on, SPLC '16, 2016. ,
DOI : 10.1109/ASE.2015.15
URL : https://hal.archives-ouvertes.fr/hal-01323446
Empirical comparison of regression methods for variability-aware performance prediction, Proceedings of the 19th International Conference on Software Product Line, SPLC '15 ,
DOI : 10.1145/2351676.2351703
Generating range fixes for software configuration, 2012 34th International Conference on Software Engineering (ICSE), 2012. ,
DOI : 10.1109/ICSE.2012.6227206