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Giving a Model-Based Testing Language a Formal Semantics via Partial MAX-SAT

Abstract : Domain-specific Languages (DSLs) are widely used in model-based testing to make the benefits of modeling available to test engineers while avoiding the problem of excessive learning effort. Complex DSLs benefit from a formal definition of their semantics for model processing as well as consistency checking. A formal semantics can be established by mapping the model domain to a well-known formalism. In this paper, we present an industrial use case which includes a mapping from domain-specific models to Moore Machines, based on a Partial MAX-SAT problem, encoding a predicative semantics for the model-to-model mapping. We show how Partial MAX-SAT solves the frame problem for a non-trivial DSL in which the non-effect on variables cannot be determined statically. We evaluated the performance of our model-transformation algorithm based on models from our industrial use case.
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https://hal.inria.fr/hal-03239819
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Submitted on : Thursday, May 27, 2021 - 4:42:43 PM
Last modification on : Thursday, May 27, 2021 - 4:58:40 PM
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Bernhard Aichernig, Christian Burghard. Giving a Model-Based Testing Language a Formal Semantics via Partial MAX-SAT. 32th IFIP International Conference on Testing Software and Systems (ICTSS), Dec 2020, Naples, Italy. pp.35-51, ⟨10.1007/978-3-030-64881-7_3⟩. ⟨hal-03239819⟩

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