Feature Model Differences

Mathieu Acher 1 Patrick Heymans 2, 3, 4 Philippe Collet 5 Clément Quinton 2 Philippe Lahire 5 Philippe Merle 2, 3
2 ADAM - Adaptive Distributed Applications and Middleware
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
4 PReCISE
Université de Lille, Sciences et Technologies, PReCISE - PReCISE Research Centre in Information Systems Engineering
5 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS
Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : Feature models are a widespread means to represent commonality and variability in software product lines. As is the case for other kinds of models, computing and managing feature model differences is useful in various real-world situations. In this paper, we propose a set of novel differencing techniques that combine syntactic and semantic mechanisms, and automatically produce meaningful differences. Practitioners can exploit our results in various ways: to understand, manipulate, visualize and reason about differences. They can also combine them with existing feature model composition and decomposition operators. The proposed automations rely on satisfiability algorithms. They come with a dedicated language and a comprehensive environment. We illustrate and evaluate the practical usage of our techniques through a case study dealing with a configurable component framework.
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Mathieu Acher, Patrick Heymans, Philippe Collet, Clément Quinton, Philippe Lahire, et al.. Feature Model Differences. CAiSE - 24th International Conference on Advanced Information Systems Engineering - 2012, Jun 2012, Gdańsk, Poland. ⟨hal-00713849v2⟩

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