Publication | Closed Access
Towards an automation of the mutation analysis dedicated to model transformation
27
Citations
35
References
2014
Year
EngineeringGeneticsSoftware SystemsTest Data GenerationSoftware EngineeringSoftware AnalysisModel Transformation TraceabilityModel-based TestingComputational TestingSystems EngineeringProgram TransformationModel-based Software DevelopmentModeling And SimulationModel Transformation LanguageTest GenerationAutomatic GenerationComputer ScienceMutation AnalysisBioinformaticsModel TransformationMutation-based TestingProgram AnalysisSoftware TestingComputational BiologyMutation OperatorsDesign For TestabilityTest EvolutionSystems BiologyMedicine
Summary A benefit of model‐driven engineering relies on the automatic generation of artefacts from high‐level models through intermediary levels using model transformations. In such a process, the input must be well designed, and the model transformations should be trustworthy. Because of the specificities of models and transformations, classical software test techniques have to be adapted. Among these techniques, mutation analysis has been ported, and a set of mutation operators has been defined. However, it currently requires considerable manual work and suffers from the test data set improvement activity. This activity is a difficult and time‐consuming job and reduces the benefits of the mutation analysis. This paper addresses the test data set improvement activity. Model transformation traceability in conjunction with a model of mutation operators and a dedicated algorithm allow to automatically or semi‐automatically produce improved test models. The approach is validated and illustrated in two case studies written in Kermeta.Copyright © 2014 John Wiley & Sons, Ltd.
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