Abstract
Abstract: Regression Testing is most imperative activity of software development life cycle. Test case prioritization being one of the most adopted branch for regression testing and with the invent of nature inspired metaheuristic techniques in optimization, this study makes an attempt to augments the features of test case prioritization with nature inspired metaheuristic techniques to determine the most efficacious metaheuristic techniques from Cuckoo Searh (CS) algorithm, Genetic Algorithm (GA) and Flower Pollination Algorithm (FPA) for three different case studies. APFD metrics is used to compare the algorithms. Further the study compares the most efficacious technique with Genetically Modified- Flower Pollination Algorithm (GM-FPA) to identify the most efficient technique for regression test case prioritization.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
