A generative approach to define rich domain-specific trace metamodels

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Abstract

Executable Domain-Specific Modeling Languages (xDSMLs) open many possibilities for performing early verification and validation (V&V) of systems. Dynamic V&V approaches rely on execution traces, which represent the evolution of models during their execution. In order to construct traces, generic trace metamodels can be used. Yet, regarding trace manipulations, they lack both efficiency because of their sequential structure, and usability because of their gap to the xDSML. Our contribution is a generative approach that defines a rich and domain-specific trace metamodel enabling the construction of execution traces for models conforming to a given xDSML. Efficiency is increased by providing a variety of navigation paths within traces, while usability is improved by narrowing the concepts of the trace metamodel to fit the considered xDSML. We evaluated our approach by generating a trace metamodel for fUML and using it for semantic differencing, which is an important V&V activity in the realm of model evolution. Results show a significant performance improvement and simplification of the semantic differencing rules as compared to the usage of a generic trace metamodel.

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Bousse, E., Mayerhofer, T., Combemale, B., & Baudry, B. (2015). A generative approach to define rich domain-specific trace metamodels. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9153, pp. 45–61). Springer Verlag. https://doi.org/10.1007/978-3-319-21151-0_4

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