Optimizing the software test case through physics-informed particle-based method

Updesh Kumar Jaiswal () and Amarjeet Prajapati ()
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Updesh Kumar Jaiswal: Jaypee Institute of Information Technology
Amarjeet Prajapati: Jaypee Institute of Information Technology

International Journal of System Assurance Engineering and Management, 2025, vol. 16, issue 2, No 4, 494-511

Abstract: Abstract Software testing relies heavily on test case reduction, which tries to lessen the number of test cases despite preserving enough coverage. This study presents a novel method named Physics-Informed Particle-based Optimization (PIPO) for improving the reduction of software test cases through the use of particle-based optimization, which is guided by physics. Particle dynamics serves as the inspiration for the suggested optimization approach, which treats test cases as particles traveling across a multidimensional space. These particles move according to physics-based principles as well as conventional optimization techniques, leading to a hybrid approach that improves solution quality and convergence efficiency. Employing experimental assessments on a range of software test cases, we illustrate the efficacy of our approach and show notable benefits in terms of decreased test suite sizes by 25% relative to baseline techniques without sacrificing test coverage. The test cases are reduced from 167 (original) to 121 (reduced) by the suggested approach. Moreover, PIPO’s competitive performance is demonstrated by a comparative analysis with the most advanced test case minimization algorithms, obtaining the reduced test set with suitable and acceptable values such as Best - 195.4 ± 5.62, Avg - 184.6 ± 3.27, and Std Dev - 2.06 ± 0.68. The results highlight the efficiency benefits attained by using physics-inspired methods, showing not just greater reduction rates but also faster convergence. Thus, incorporating PIPO into software testing can offer a promising avenue for achieving more efficient and effective test case minimization strategies.

Keywords: Test suite reduction; Nature-inspired optimization; Software testing; Physics-informed principle; Parameter optimization (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13198-024-02663-7

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