On extracting relevant and complex variability information from software descriptions with pattern structures

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 : The migration from existing software variants to a software product line is an arduous task that necessitates to synthesise a variability model based on already developed softwares. Nowadays, the increasing complexity of software product lines compels practitioners to design more complex variability models that represent other information than binary features, e.g., multi-valued attributes. Assisting the extraction of complex variability models from variant descriptions is a key task to help the migration towards complex software product lines. In this paper, we address the problem of extracting complex variability information from software descriptions , as a part of the process of complex variability model synthesis. We propose an approach based on Pattern Structures to extract variability information, in the form of logical relationships involving both binary features and multi-valued attributes.
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ICSE: International Conference on Software Engineering, May 2018, Gothenburg, Sweden. ACM Press, 40th International Conference on Software Engineering: Companion Proceeedings, 2, pp.304-305, 2018, 〈https://www.icse2018.org〉. 〈10.1145/3183440.3194982〉
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Soumis le : mercredi 12 septembre 2018 - 14:54:59
Dernière modification le : mercredi 19 septembre 2018 - 01:14:32

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Jessie Carbonnel, Marianne Huchard, Clémentine Nebut. On extracting relevant and complex variability information from software descriptions with pattern structures. ICSE: International Conference on Software Engineering, May 2018, Gothenburg, Sweden. ACM Press, 40th International Conference on Software Engineering: Companion Proceeedings, 2, pp.304-305, 2018, 〈https://www.icse2018.org〉. 〈10.1145/3183440.3194982〉. 〈lirmm-01872807〉

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