An Efficient Regression Test Cases Selection & Optimization Using Mayfly Optimization Algorithm

Abhishek Singh Verma (), Ankur Choudhary (), Shailesh Tiwari () and Bhuvan Unhelkar ()
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Abhishek Singh Verma: Dr. APJ Abdul Kalam Technical University
Ankur Choudhary: Sharda University
Shailesh Tiwari: ABES Engineering College
Bhuvan Unhelkar: Universitu of South Florida

A chapter in Predictive Analytics in System Reliability, 2023, pp 119-135 from Springer

Abstract: Abstract Testing has been an inevitable activity in the software development life cycle. In the current scenario, software development has become evolutionary in nature where software is released in cycles, each cycle fulfilling the requirements of the customer on a priority basis. This evolutionary development of software also demands high maintenance in the form of retesting. This re-testing is called regression testing and the literature reveals that it is a proven N-P hard problem that attracts the application of approximation algorithms such as meta-heuristics. In this paper, Mayfly Optimization Algorithm has been adopted to solve the regression test case selection problem to minimize the maintenance cost. The aim is to optimize the number of test cases to re-execute to reduce the execution time and cost. The performance of the adopted approach is further compared with state-of-the-art approaches with the help of statistical tests. The shows that the adopted approach performs well in comparison to state of art approaches.

Keywords: Software testing; Mayfly optimization algorithm; SIR; MetaHeuristics; Regression test case selection (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-031-05347-4_8

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DOI: 10.1007/978-3-031-05347-4_8

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