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9th IEEE International Conference on Software testing, Verification and Validation (ICST)

作者： Al-Refai, Mohammed Ghosh, Sudipto Cazzola, Walter Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA Univ Milan Dept Comp Sci Milan Italy

ISBN: (纸本)9781509018277

An increasing number of modern software systems need to be adapted at runtime without stopping their execution. Runtime adaptations can introduce faults in existing functionality, and thus, regression testing must be conducted after an adaptation is performed but before the adaptation is deployed to the running system. regression testing must be completed subject to time and resource constraints. Thus, test selection techniques are needed to reduce the cost of regression testing. The FiGA framework provides a complete loop from code to models and back that allows fine-grained model-based adaptation and validation of running Java systems without stopping their execution. In this paper we present a model-based test selection approach for regression testing during the validation activity to be used with the FiGA framework. The evaluation results show that our approach was able to reduce the number of selected test cases, and that the model-level fault detection ability of the selected test cases was never lower than that of the original test cases.

关键词： model-based regression test selection model-based validation model-based dynamic adaptation executable UML models JUnit tests unanticipated adaptation

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Supporting inheritance hierarchy changes in model-based regression test selection

引用

SOFTWARE AND SYSTEMS modelING 2019年第2期18卷 937-958页

作者： Al-Refai, Mohammed Ghosh, Sudipto Cazzola, Walter Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA Univ Milan Dept Comp Sci Milan Italy

models can be used to ease and manage the development, evolution, and runtime adaptation of a software system. When models are adapted, the resulting models must be rigorously tested. Apart from adding new test cases, it is also important to perform regression testing to ensure that the evolution or adaptation did not break existing functionality. Since regression testing is performed with limited resources and under time constraints, regression test selection (RTS) techniques are needed to reduce the cost of regression testing. Applying model-level RTS for model-based evolution and adaptation is more convenient than using code-level RTS because the test selection process happens at the same level of abstraction as that of evolution and adaptation. In earlier work, we proposed a model-based RTS approach called MaRTS to be used with a fine-grained model-based adaptation framework that targets applications implemented in Java. MaRTS uses UML models consisting of class and activity diagrams. It classifies test cases as obsolete, reusable, or retestable based on changes made to UML class and activity diagrams of the system being adapted. However, MaRTS did not take into account the changes made to the inheritance hierarchy in the class diagram and the impact of these changes on the selection of test cases. This paper extends MaRTS to support such changes and demonstrates that the extended approach performs as well as or better than code-based RTS approaches in safely selecting regression test cases. While MaRTS can generally be used during any model-driven development or model-based evolution activity, we have developed it in the context of runtime adaptation. We evaluated the extended MaRTS on a set of applications and compared the results with code-based RTS approaches that also support changes to the inheritance hierarchy. The results showed that the extended MaRTS selected all the test cases relevant to the inheritance hierarchy changes and that the fault detection

关键词： Executable UML models Inheritance hierarchy model-based adaptation model-based regression test selection model validation Runtime adaptation UML activity diagram UML class diagram

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