Search-based Similarity-driven Behavioural SPL Testing

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Résumé

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 behavioural SPL models, especially on the largest case-study where no other approach can match it.
langue originaleAnglais
titreProceedings of the Tenth International Workshop on Variability Modelling of Software-intensive Systems
Lieu de publicationSalvador of Bahia, Brazil
EditeurACM Press
Pages89-96
Nombre de pages8
ISBN (imprimé)978-1-4503-4019-9
Les DOIs
Etat de la publicationPublié - 27 janv. 2016

Série de publications

NomVaMoS '16
EditeurACM

    Empreinte digitale

Contient cette citation

Devroey, X., Perrouin, G., Legay, A., Schobbens, P-Y., & Heymans, P. (2016). Search-based Similarity-driven Behavioural SPL Testing. Dans Proceedings of the Tenth International Workshop on Variability Modelling of Software-intensive Systems (p. 89-96). (VaMoS '16). ACM Press. https://doi.org/10.1145/2866614.2866627