P
Philippe Collet
Researcher at Centre national de la recherche scientifique
Publications - 125
Citations - 2030
Philippe Collet is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Feature model & Software product line. The author has an hindex of 21, co-authored 116 publications receiving 1856 citations. Previous affiliations of Philippe Collet include University of Nice Sophia Antipolis.
Papers
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Journal ArticleDOI
FAMILIAR: A domain-specific language for large scale management of feature models
TL;DR: FAMILIAR is presented as a Domain-Specific Language (DSL) that is dedicated to the large scale management of feature models and that complements existing tool support and demonstrates their applicability to different domains and use for different purposes.
Proceedings ArticleDOI
On extracting feature models from product descriptions
Mathieu Acher,Anthony Cleve,Gilles Perrouin,Patrick Heymans,Charles Vanbeneden,Philippe Collet,Philippe Lahire +6 more
TL;DR: This paper aims at easing the transition from product descriptions expressed in a tabular format to FMs accurately representing them, and guarantees that the resulting FM represents the set of legal feature combinations supported by the considered products and has a readable tree hierarchy together with variability information.
Book ChapterDOI
The relevance of model-driven engineering thirty years from now
Gunter Mussbacher,Daniel Amyot,Ruth Breu,Jean-Michel Bruel,Betty H. C. Cheng,Philippe Collet,Benoit Combemale,Rogardt Heldal,James Hill,Jörg Kienzle,Matthias Schöttle,Friedrich Steimann,Dave R. Stikkolorum,Jon Whittle +13 more
TL;DR: A reflection of the current strengths of MDE, an outlook of the most pressing challenges for society at large over the next three decades, and an analysis of key future MDE research opportunities are presented.
Book ChapterDOI
Composing feature models
TL;DR: This paper proposes a set of composition operators dedicated to feature models that enable the development of large feature models by composing smaller feature models which address well-defined concerns.
Book ChapterDOI
Reverse engineering architectural feature models
TL;DR: This paper develops automated techniques to extract and combine different variability descriptions of an architecture, and applies alignment and reasoning techniques to integrate the architect knowledge and reinforce the extracted FM.