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Testing Models and Model Transformations Using Classifying Terms

Título: Testing Models and Model Transformations Using Classifying TermsAutores: Frank Hilken, Martin Gogolla, Loli Burgueño, Antonio VallecilloRevista: Software and System Modeling (Sosym)Número: 17(3)Fecha de publicación: Julio 2018Páginas: 885-912DOI: 10.1007/s10270-016-0568-3Indicios de calidad:-Factor de impacto: 1.722 (Q2)- Número de citas: 16 (según GSholar)

Automated inference of likely metamorphic relations for model transformations (YA PUBLICADO)

Model transformations play a cornerstone role in Model-Driven Engineering (MDE) as they provide the essential mechanisms for manipulating and transforming models. Checking whether the output of a model transformation is correct is a manual and errorprone task, referred to as the oracle problem. Metamorphic testing alleviates the oracle problem by exploiting the relations among different inputs and outputs of the program under test, so-called metamorphic relations (MRs). One of the main challenges in metamorphic testing is the automated inference of likely MRs. This paper proposes an approach to automatically infer likely MRs for ATL model transformations, where the tester does not need to have any knowledge of the transformation. The inferred MRs aim at detecting faults in model transformations in three application scenarios, namely regression testing, incremental transformations and migrations among transformation languages. In the experiments performed, the inferred likely MRs have proved to be quite accurate, with a precision of 96.4% from a total of 4101 true positives out of 4254 MRs inferred. Furthermore, they have been useful for identifying mutants in regression testing scenarios, with a mutation score of 93.3%. Finally, our approach can be used in conjunction with current approaches for the automatic generation of test cases. Artículo publicado en The Journal of Systems and Software, Vol 136, pp 188-208 (Available Online May 2017; Final Published Version February 2018) – Q1.

On the Modular Specification of NFPs: A Case Study

The modular specification of non-functional properties of systems is a current challenge of Software Engineering, for which no clear solution exists. However, in the case of Domain-Specific Languages some successful proposals are starting to emerge, combining model-driven techniques with aspect-weaving mechanisms. In this paper we show one of these approaches in practice, and present the implementation we have developed to fully support it. We apply our approach for the specification and monitoring of non-functional properties using observers to a case study, illustrating how generic observers defining nonfunctional properties can be defined in an independent manner. Then, correspondences between these observers and the domain-specific model of the system can be established, and then weaved into a unified system specification using an ATL model transformation. Such a unified specification can also be analyzed in a natural way to obtain the required non-functional properties of the system.