Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/13618
Title: Application of the law of minimum and dissimilarity analysis to regression test case prioritization
Authors: Ufuktepe, Ekincan
Tuğlular, Tuğkan
Keywords: Change impact analysis
Regression testing
Software testing
Test case prioritization
Mutation
Publisher: IEEE
Abstract: Regression testing is one of the most expensive processes in testing. Prioritizing test cases in regression testing is critical for the goal of detecting the faults sooner within a large set of test cases. We propose a test case prioritization (TCP) technique for regression testing called LoM-Score inspired by the Law of Minimum (LoM) from biology. This technique calculates the impact probabilities of methods calculated by change impact analysis with forward slicing and orders test cases according to LoM. However, this ordering doesn't consider the possibility that consecutive test cases may be covering the same methods repeatedly. Thereby, such ordering can delay the time of revealing faults that exist in other methods. To solve this problem, we enhance the LoM-Score TCP technique with an adaptive approach, namely with a dissimilarity-based coordinate analysis approach. The dissimilarity-based coordinate analysis uses Jaccard Similarity for calculating the similarity coefficients between test cases in terms of covered methods and the enhanced technique called Dissimilarity-LoM-Score (Dis-LoM-Score) applies a penalty with respective on the ordered test cases. We performed our case study on 10 open-source Java projects from Defects4J, which is a dataset of real bugs and an infrastructure for controlled experiments provided for software engineering researchers. Then, we hand-seeded multiple mutants generated by Major, which is a mutation testing tool. Then we compared our TCP techniques LoM-Score and Dis-LoM-Score with the four traditional TCP techniques based on their Average Percentage of Faults Detected (APFD) results.
URI: https://doi.org/10.1109/ACCESS.2023.3283212
https://hdl.handle.net/11147/13618
ISSN: 2169-3536
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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