HOTCP: Hybrid Optimal Test Case Prioritisation with Multi-Objective Constraints

Mukund Baburao Wagh, Vishal V. Puri, Sanjay B. Waykar and Rajesh Kadu
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Mukund Baburao Wagh: Department of Computer Engineering, Trinity Academy of Engineering, Pune, Maharashtra 411048, India
Vishal V. Puri: Department of Computer Engineering, School of Engineering & Technology, DY Patil University, Ambi, Pune, India
Sanjay B. Waykar: Department of Information Technology, Mahatma Gandhi Mission’s College of Engineering and Technology, Navi Mumbai, Maharashtra, India
Rajesh Kadu: Department of Computer Engineering, Mahatma Gandhi Mission’s College of Engineering and Technology, Navi Mumbai, Maharashtra, India

Journal of Information & Knowledge Management (JIKM), 2024, vol. 23, issue 03, 1-24

Abstract: As a result of late detection and resource limitations during any software evaluation, there have been several software-related breakdowns or malfunctions. Many people have begun focussing on the test cases or alternatively the priority of validation suites after identifying the difficulties in the regression testing process of any product. The test case prioritisation technique is presented as a solution to this problem. It increases the fault detection rate. Earlier research studies have been implemented many techniques, but the rate of fault detection is not up to the mark. To overcome this drawback, we proposed HOTCP (Hybrid Optimal Test Case Prioritisation with Multi-Objective Constraints) model, which includes two steps: first is test case generation and the next one is test case prioritisation. The test case is generated from the released software. Consequently, test case prioritisation will be done by the optimisation strategy, in which the multi-objective function will be defined based on the constraints like statement coverage, branch coverage, contribution index and fault exposing potential. For this optimisation process, a new algorithm is proposed termed as CCCOA (Customised Coot and Chimp Optimisation Algorithm). The COOT optimisation and Chimp optimisation algorithms are combined in this algorithm. The system produces prioritised test cases, and the performance of the proposed method is validated in comparison to the traditional methods in terms of several metrics.

Keywords: Statement coverage; fault exposing potential; branch coverage; contribution index (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219649224500126

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