Sutapa, Fransiskus Anindita Kristiawan Pramana Gentur and Kusumawardani, Sri Suning and Permanasari, Adhistya Erna (2020) A Review of Automated Testing Approach for Software Regression Testing. In: International Conference on Applied Sciences, Information and Technology 2019, 1-3 November 2019, Padang, Indonesia.
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Abstract
One of the important parts of software development life-cycle is software testing and one of which is regression testing. Regression testing is done to verify that previously detected errors have been corrected correctly and no new errors arise as a result of incorrect corrections so that the quality of the software being tested is maintained. It is important and must be done. However, the conventional method is not efficient as it is time-consuming, not reusable, and prone to error. In this paper, a comprehensive review of the automated testing approach is presented to be used by other researchers in this field of study. The review result shows that the automated testing approach is suitable to enhance the regression testing with some plausible options of tools e.g. Selenium, SAHI, and Robot-framework. Furthermore, some plausible options of execution methods are also discussed in this paper. This review further concludes that the parallel execution method is considered as a promising choice to conduct the most efficient regression testing process. © Published under licence by IOP Publishing Ltd.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Cited by: 1; Conference name: International Conference on Applied Sciences, Information and Technology 2019, ICo-ASCNITech 2019; Conference date: 1 November 2019 through 3 November 2019; Conference code: 160696; All Open Access, Gold Open Access |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Electrical and Information Technology Department |
| Depositing User: | Sri JUNANDI |
| Date Deposited: | 14 Aug 2025 06:32 |
| Last Modified: | 14 Aug 2025 06:32 |
| URI: | https://ir.lib.ugm.ac.id/id/eprint/16773 |
