Testing Variability-Intensive Systems

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Résumé

Cost-effective techniques to test software in the presence of variability are popular in academia but are not systematically applied in practice yet. This half-day tutorial offers an overview of the state of the art of some of the hottest topics in the field such as (dis)similarity & search-based testing, model-based testing or mutation analysis. We will present the most significant results obtained during the last five years ranging from conceptual foundations to readily usable tools. In particular, we will rely on VIBeS, a model-based open source framework we developed to test product lines behaviour. We will illustrate all these concepts on JHipster, a variability-intensive web development stack.
langue originaleAnglais
titreSPLC 2017 - 21st International Systems and Software Product Line Conference, Proceedings
rédacteurs en chefLidia Fuentes, Ebrahim Bagheri, Antonio Ruiz-Cortes, David Benavides, Rafael Capilla, Yingfei Xiong, Jan Bosch, Mathieu Acher, Daniel Schall, Myra Cohen, Javier Troya
Lieu de publicationNew York, New York, USA
EditeurACM Press
Pages255-255
Nombre de pages1
Volume1
ISBN (Electronique)9781450352215
Les DOIs
étatPublié - 26 sept. 2017
Evénement21st International Systems and Software Product Line Conference (SPLC '17) - Sevilla, Espagne
Durée: 25 sept. 201729 sept. 2017
http://congreso.us.es/splc2017/

Série de publications

NomSPLC '17
EditeurACM

Une conférence

Une conférence21st International Systems and Software Product Line Conference (SPLC '17)
Titre abrégéSPLC '17
PaysEspagne
La villeSevilla
période25/09/1729/09/17
Adresse Internet

    Empreinte digitale

Contient cette citation

Perrouin, G., Devroey, X., & Cordy, M. (2017). Testing Variability-Intensive Systems. Dans L. Fuentes, E. Bagheri, A. Ruiz-Cortes, D. Benavides, R. Capilla, Y. Xiong, J. Bosch, M. Acher, D. Schall, M. Cohen, ... J. Troya (eds.), SPLC 2017 - 21st International Systems and Software Product Line Conference, Proceedings (Vol 1, p. 255-255). (SPLC '17). New York, New York, USA: ACM Press. https://doi.org/10.1145/3106195.3106226