Search-based Similarity-driven Behavioural SPL Testing

Abstract : Dissimilar test cases have been proven to be effective to reveal faults in software systems. In the Software Product Line (SPL) context, this criterion has been applied successfully to mimic combinatorial interaction testing in an efficient and scalable manner by selecting and prioritising most dissimilar configurations of feature models using evolutionary algorithms. In this paper, we extend dissimilarity to behavioural SPL models (FTS) in a search-based approach, and evaluate its effectiveness in terms of product and fault coverage. We investigate different distances as well as as single-objective algorithms, (dissimilarity on actions, random , all-actions). Our results on four case studies show the relevance of dissimilarity-based test generation for be-havioural SPL models, especially on the largest case-study where no other approach can match it.
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VaMoS '16 - Tenth International Workshop on Variability Modelling of Software-intensive Systems, Jan 2016, Salvador, Brazil. ACM, pp.89 - 96, 2016, 〈10.1145/2866614.2866627〉
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Soumis le : jeudi 1 décembre 2016 - 14:32:08
Dernière modification le : mercredi 11 avril 2018 - 01:51:20

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Xavier Devroey, Gilles Perrouin, Axel Legay, Pierre-Yves Schobbens, Patrick Heymans. Search-based Similarity-driven Behavioural SPL Testing. VaMoS '16 - Tenth International Workshop on Variability Modelling of Software-intensive Systems, Jan 2016, Salvador, Brazil. ACM, pp.89 - 96, 2016, 〈10.1145/2866614.2866627〉. 〈hal-01406585〉

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