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Multi-criteria test cases selection for model transformations

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Abstract

Model transformations play an important role in the evolution of systems in various fields such as healthcare, automotive and aerospace industry. Thus, it is important to check the correctness of model transformation programs. Several approaches have been proposed to generate test cases for model transformations based on different coverage criteria (e.g., statements, rules, metamodel elements, etc.). However, the execution of a large number of test cases during the evolution of transformation programs is time-consuming and may include a lot of overlap between the test cases. In this paper, we propose a test case selection approach for model transformations based on multi-objective search. We use the non-dominated sorting genetic algorithm (NSGA-II) to find the best trade-offs between two conflicting objectives: (1) maximize the coverage of rules and (2) minimize the execution time of the selected test cases. We validated our approach on several evolution cases of medium and large ATLAS Transformation Language programs.

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Notes

  1. http://www.eclipse.org/atl.

  2. https://www.eclipse.org/atl/atlTransformations/BibTeXML2DocBook/ExampleBibTeXML2DocBook[v00.01].pdf.

  3. https://github.com/javitroya/SBFL_MT.

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Acknowledgements

This work has been partially supported and funded by the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development and by the FWF under the Grant Numbers P28519-N31 and P30525-N31.

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  1. University of Michigan, Dearborn, USA

    Bader Alkhazi, Chaima Abid & Marouane Kessentini

  2. CDL-MIssNT, Johannes Kepler University, Linz, Austria

    Dorian Leroy & Manuel Wimmer

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Alkhazi, B., Abid, C., Kessentini, M. et al. Multi-criteria test cases selection for model transformations. Autom Softw Eng 27, 91–118 (2020). https://doi.org/10.1007/s10515-020-00271-w

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