Model-Based Regression Test Selection for Validating Runtime Adaptation of Software Systems

• Published in: 2016 IEEE International Conference on Software Testing, Verification and Validation (ICST) pp. 288 - 298
• Main Authors: Al-Refai, Mohammed, Ghosh, Sudipto, Cazzola, Walter
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2016
• Subjects: Adaptation models; Analytical models; executable UML models; Java; JUnit tests; model-based dynamic adaptation; model-based regression test selection; model-based validation; Runtime; Software systems; Testing; unanticipated adaptation; Unified modeling language
• DOI: 10.1109/ICST.2016.24

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.