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Fault Coverage-Based Test Case Prioritization and Selection Using African Buffalo Optimization

Shweta Singhal1, Nishtha Jatana2, Ahmad F Subahi3, Charu Gupta4,*, Osamah Ibrahim Khalaf5, Youseef Alotaibi6

1 Indira Gandhi Delhi Technical University for Women, Delhi, 110006, India
2 Maharaja Surajmal Institute of Technology, New Delhi, 110058, India
3 Department of Computer Science, University College of Al Jamoum, Umm Al-Qura University, Makkah, 21421, Saudi Arabia
4 Bhagwan Parshuram Institute of Technology, Rohini, New Delhi, 110085, India
5 Al-Nahrain University, Al-Nahrain Nanorenewable Energy Research Center, Baghdad, 64074, Iraq
6 Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah, 21955, Saudi Arabia

* Corresponding Author: Charu Gupta. Email: email

Computers, Materials & Continua 2023, 74(3), 6755-6774. https://doi.org/10.32604/cmc.2023.032308

Abstract

Software needs modifications and requires revisions regularly. Owing to these revisions, retesting software becomes essential to ensure that the enhancements made, have not affected its bug-free functioning. The time and cost incurred in this process, need to be reduced by the method of test case selection and prioritization. It is observed that many nature-inspired techniques are applied in this area. African Buffalo Optimization is one such approach, applied to regression test selection and prioritization. In this paper, the proposed work explains and proves the applicability of the African Buffalo Optimization approach to test case selection and prioritization. The proposed algorithm converges in polynomial time (O(n2)). In this paper, the empirical evaluation of applying African Buffalo Optimization for test case prioritization is done on sample data set with multiple iterations. An astounding 62.5% drop in size and a 48.57% drop in the runtime of the original test suite were recorded. The obtained results are compared with Ant Colony Optimization. The comparative analysis indicates that African Buffalo Optimization and Ant Colony Optimization exhibit similar fault detection capabilities (80%), and a reduction in the overall execution time and size of the resultant test suite. The results and analysis, hence, advocate and encourages the use of African Buffalo Optimization in the area of test case selection and prioritization.

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Cite This Article

APA Style
Singhal, S., Jatana, N., Subahi, A.F., Gupta, C., Khalaf, O.I. et al. (2023). Fault coverage-based test case prioritization and selection using african buffalo optimization. Computers, Materials & Continua, 74(3), 6755-6774. https://doi.org/10.32604/cmc.2023.032308
Vancouver Style
Singhal S, Jatana N, Subahi AF, Gupta C, Khalaf OI, Alotaibi Y. Fault coverage-based test case prioritization and selection using african buffalo optimization. Comput Mater Contin. 2023;74(3):6755-6774 https://doi.org/10.32604/cmc.2023.032308
IEEE Style
S. Singhal, N. Jatana, A.F. Subahi, C. Gupta, O.I. Khalaf, and Y. Alotaibi "Fault Coverage-Based Test Case Prioritization and Selection Using African Buffalo Optimization," Comput. Mater. Contin., vol. 74, no. 3, pp. 6755-6774. 2023. https://doi.org/10.32604/cmc.2023.032308



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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