@inproceedings{9bd96f995fd84bef8663bef625ed3c72,
title = "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.",
keywords = "Consistency checking, Formal semantics, Frame problem, Model transformation, Partial MAX-SAT, Partial moore machines",
author = "Bernhard Aichernig and Christian Burghard",
year = "2020",
doi = "10.1007/978-3-030-64881-7_3",
language = "English",
isbn = "978-3-030-64880-0",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "35--51",
editor = "Valentina Casola and {De Benedictis}, Alessandra and Massimiliano Rak",
booktitle = "Testing Software and Systems - 32nd IFIP WG 6.1 International Conference, ICTSS 2020, Proceedings",
note = "32nd IFIP International Conference on Testing Software and Systems : ICTSS 2020, IFIP-ICTSS 2020 ; Conference date: 09-12-2020 Through 11-12-2020",
}