Abstract
TESTAR is a traversal-based and scriptless tool for test automation at the Graphical User Interface (GUI) level. It is different from existing test approaches because no test cases need to be defined before testing. Instead, the tests are generated during the execution, on-the-fly. This paper presents an empirical case study in a realistic industrial context where we compare TESTAR to a manual test approach of a web-based application in the rail sector. Both qualitative and quantitative research methods are used to investigate learnability, effectiveness, efficiency, and satisfaction. The results show that TESTAR was able to detect more faults and higher functional test coverage than the used manual test approach. As far as efficiency is concerned, the preparation time of both test approaches is identical, but TESTAR can realize test execution without the use of human resources. Finally, TESTAR turns out to be a learnable test approach. As a result of the study described in this paper, TESTAR technology was successfully transferred and the company will use both test approaches in a complementary way in the future.
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JSF is a Java-based component to build a GUI.
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Acknowledgments
We would like to acknowledge the help of the case study companies They have been supporting our research, answering our questions, and validating our analyses. We would also like to thank the involved universities. This work was partially funded by the ITEA3 TESTOMAT project and the H2020 DECODER project.
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Chahim, H., Duran, M., Vos, T.E.J., Aho, P., Condori Fernandez, N. (2020). Scriptless Testing at the GUI Level in an Industrial Setting. In: Dalpiaz, F., Zdravkovic, J., Loucopoulos, P. (eds) Research Challenges in Information Science. RCIS 2020. Lecture Notes in Business Information Processing, vol 385. Springer, Cham. https://doi.org/10.1007/978-3-030-50316-1_16
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