Analyzing Variability in Product Families through Canonical Feature Diagrams

Jessie Carbonnel 1 Marianne Huchard 1 Clémentine Nebut 1
1 MAREL - Models And Reuse Engineering, Languages
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Product line engineering aims to reduce the cost and effort to develop new related softwares, while increasing the software quality and the software scope. Variability analysis and modeling is a key issue in this approach. Several representations were proposed, including feature models (FMs) and product comparison matrices (PCMs). While PCMs are useful for presenting products in a tabular form, for their understanding and manipulation, it helps to switch to a graphical view. FMs are graphical views, but they are not canonical (i.e., several equivalent FMs can represent a same PCM) and user intervention is necessary to ensure the extraction of a meaningful FM from PCMs. In this paper, we investigate the benefits of a new structure, which captures variability in a canonical graphical representation. We outline its construction and we give insights about its shape and use when it is used as an alternative representation of wikipedia PCMs in the domain of software.
Keywords : Product lines Product Comparison Matrix Feature Model Formal Concept Analysis
Type de document :
Communication dans un congrès
Xudong He. SEKE: Software Engineering & Knowledge Engineering, Jul 2017, Pittsburgh, PA, United States. KSI research Inc., 29th International Conference on Software Engineering & Knowledge Engineering, 2017, pp.185-190, 2017, 〈http://ksiresearchorg.ipage.com/seke/seke17.html〉. 〈10.18293/SEKE2017-087〉
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Jessie Carbonnel, Marianne Huchard, Clémentine Nebut. Analyzing Variability in Product Families through Canonical Feature Diagrams. Xudong He. SEKE: Software Engineering & Knowledge Engineering, Jul 2017, Pittsburgh, PA, United States. KSI research Inc., 29th International Conference on Software Engineering & Knowledge Engineering, 2017, pp.185-190, 2017, 〈http://ksiresearchorg.ipage.com/seke/seke17.html〉. 〈10.18293/SEKE2017-087〉. 〈lirmm-01621104〉

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