State machine flattening, a mapping study and tools assessment

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Résumé

State machine formalisms equipped with hierarchy and parallelism allow to compactly model complex system behaviours. Such models can then be transformed into executable code or inputs for model-based testing and verification techniques. Generated artifacts are mostly flat descriptions of system behaviour. Flattening is thus an essential step of these transformations. To assess the importance of flattening, we have defined and applied a systematic mapping process and 30 publications were finally selected. However, it appeared that flattening is rarely the sole focus of the publications and that care devoted to the description and validation of flattening techniques varies greatly. Preliminary assessment of associated tool support indicated limited tool availability and scalability on challenging models. We see this initial investigation as a first step towards generic flattening techniques and scalable tool support, cornerstones of reliable model-based behavioural development.

langue originaleAnglais
titre2015 IEEE 8th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2015 - Proceedings
Sous-titreA-MOST '15
EditeurIEEE
Pages1-8
Nombre de pages8
ISBN (imprimé)9781479918850
Les DOIs
étatPublié - 13 mai 2015
Evénement2015 8th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2015 - Graz, Autriche
Durée: 13 avr. 201517 avr. 2015

Une conférence

Une conférence2015 8th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2015
PaysAutriche
La villeGraz
période13/04/1517/04/15

    Empreinte digitale

Contient cette citation

Devroey, X., Cordy, M., Schobbens, P. Y., Legay, A., & Heymans, P. (2015). State machine flattening, a mapping study and tools assessment. Dans 2015 IEEE 8th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2015 - Proceedings: A-MOST '15 (p. 1-8). [7107408] IEEE. https://doi.org/10.1109/ICSTW.2015.7107408