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Test Cases Prioritization Using Ant Colony Optimization and Firefly Algorithm

Test Cases Prioritization Using Ant Colony Optimization and Firefly Algorithm
	© 2022 by IJETT Journal
	Volume-70 Issue-3
	Year of Publication : 2022
	Authors : Muhammad Afiq Ariffin, Rosziati Ibrahim, Izrulfizal Saufihamizal Ibrahim, Jahari Abdul Wahab
	https://doi.org/10.14445/22315381/IJETT-V70I3P203

How to Cite?

Muhammad Afiq Ariffin, Rosziati Ibrahim, Izrulfizal Saufihamizal Ibrahim, Jahari Abdul Wahab, "Test Cases Prioritization Using Ant Colony Optimization and Firefly Algorithm," International Journal of Engineering Trends and Technology, vol. 70, no. 3, pp. 22-28, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I3P203

Abstract
A software testing process is the most complex and important part to be considered in the software development life cycle. This testing process usually takes a lot of time and is also very costly. The modification that has been made must also not affect the other unmodified parts of the software. Regression testing is the most suitable function that can be used for the software testing process, and the method includes the prioritization of test cases. There are several techniques in the prioritization of test cases, and most of the techniques are inspired by nature, such as Ant Colony Optimization (ACO) and Firefly Algorithm (FA). This paper will look at ACO and FA techniques for the prioritization of test cases. These techniques will be executed to identify the performance of each technique, which will be evaluated based on the Average Percentage of Faults Detected (APFD), execution time, and fault coverage. Based on the evaluation results, it showed that the FA technique recorded the lowest execution time and achieved a 100% of fault coverage.

Keywords
Software testing, Prioritization of test cases, ant colony optimization, Firefly algorithm.

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