[PhD Thesis Defense] Automated Test Generation for production systems with a Model-based Testing approach
This thesis tackles the problem of testing (legacy) production systems such as those of our industrial partner Michelin, one of the three largest tire manufacturers in the world, by means of Model-based Testing.
people” Test: “the means by which the quality of anything is determined” Generation: “the act or process of generating” (for) production systems: “a set of production machines controlled by a software (or application)” (with a) Model-based Testing approach
several issues with our Level 2 applications.” “Some of them are not covered by tests. We have many legacy applications and we would like to avoid regressions.” “We have outdated documentation we cannot rely on.” “These applications run in our factories for years, but we can state that they behave correctly in production.”
Inférence de modeles dirigée par la logique métier. In Actes de la 13eme édition d’AFADL, atelier francophone sur les Approches Formelles dans l’Assistance au Développement de Logiciels. Durand, W., & Salva, S. (2014). Inferring models with rule-based expert systems. In Proceedings of the Fifth Symposium on Information and Communication Technology (pp. 92-101). ACM. Salva, S., & Durand, W. (2015). Autofunk, a fast and scalable framework for building formal models from production systems. In Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems (pp. 193-204). ACM. Durand, W., & Salva, S. (2015). Autofunk: An Inference-Based Formal Model Generation Framework for Production Systems. In FM 2015: Formal Methods (pp. 577-580). Springer International Publishing. Durand, W., & Salva, S. (2015). Passive testing of production systems based on model inference. In Formal Methods and Models for Codesign (MEMOCODE), 2015 ACM/IEEE International Conference on (pp. 138-147). IEEE. 2 under submissions (ACM CSUR, JSS)
information with physical devices and machines by sending and receiving production events Michelin's exchanging systems guarantee the order in which the production events occured Events can be captured directly into these systems to avoid loss, reordering, and/or duplication of the events
to a product (e.g., a tire), identified by a product identifier ( ). Gathering all production events related to a product allows to retrieve what happened to it (behaviors). q That is what Michelin experts use to do.
... D1 3,851,264 73,364 35,541 924 D2 17,402 837 E1 7,635,494 134,908 61,795 1,441 E2 35,799 1,401 F1 9,231,160 161,035 77,058 1,587 F2 43,536 1,585 q It took 5 minutes to build the two models of experiment F.
learning, and expert systems to infer models for web applications and production systems (Autofunk) Offline passive testing for production systems on-top of Autofunk, along with two implementation relations An implementation of Autofunk for Michelin