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

In: Predictive Analytics in System Reliability

Author

Listed:
  • Abhishek Singh Verma

    (Dr. APJ Abdul Kalam Technical University
    Sharda University)

  • Ankur Choudhary

    (Sharda University)

  • Shailesh Tiwari

    (ABES Engineering College)

  • Bhuvan Unhelkar

    (Universitu of South Florida)

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.

Suggested Citation

  • Abhishek Singh Verma & Ankur Choudhary & Shailesh Tiwari & Bhuvan Unhelkar, 2023. "An Efficient Regression Test Cases Selection & Optimization Using Mayfly Optimization Algorithm," Springer Series in Reliability Engineering, in: Vijay Kumar & Hoang Pham (ed.), Predictive Analytics in System Reliability, pages 119-135, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-05347-4_8
    DOI: 10.1007/978-3-031-05347-4_8
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