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Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines

Contributo in Atti di convegno
Data di Pubblicazione:
2019
Citazione:
(2019). Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines . Retrieved from http://hdl.handle.net/10446/150840
Abstract:
In this paper we propose a new approach to conformance testing based on Abstract State Machine (ASM) model refinement. It consists in generating test sequences from ASM models and checking the conformance between code and models in multiple iterations. This process is applied at different models, starting from the more abstract model to the one that is very close to the code. The process consists of the following steps: (1) model the system as an Abstract State Machine, (2) generate test sequences based on the ASM model, (3) compute the code coverage using generated tests, (4) if the coverage is low refine the Abstract State Machine and return to step 2. We have applied the proposed approach to Antidote, an open-source implementation of IEEE 11073-20601 Personal Health Device (PHD) protocol which allows personal healthcare devices to exchange data with other devices such as small computers and smartphones.
Tipologia CRIS:
1.4.01 Contributi in atti di convegno - Conference presentations
Elenco autori:
Bombarda, Andrea; Bonfanti, Silvia; Gargantini, Angelo Michele; Radavelli, Marco; Duan, Feng; Lei, Yu
Autori di Ateneo:
BOMBARDA Andrea
BONFANTI Silvia
GARGANTINI Angelo Michele
Link alla scheda completa:
https://aisberg.unibg.it/handle/10446/150840
Titolo del libro:
Testing Software and Systems: 31st IFIP WG 6.1 International Conference, ICTSS 2019, Paris, France, October 15–17, 2019, Proceedings
Pubblicato in:
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
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