Enhanced Wingsuit Flying Search (EWFS) Algorithm for Combinatorial T-way Test Suite Generation

  • Nurol Husna Che Rose Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia https://orcid.org/0009-0009-1741-7076
  • Rozmie Razif Othman Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia
  • Hasneeza Liza Zakaria Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia
  • Anjila J Suali Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia
  • Husna Jamal Abdul Nasir Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia
  • Jalal Altmemi Information Technology Management Department, Southern Technical University, Basrah, Iraq
DOI: https://doi.org/10.24003/emitter.v13i2.979
Keywords: Combinatorial testing, T-way testing, Wingsuit Flying Search (WFS) Algorithm, Optimization

Abstract

The Wingsuit Flying Search (WFS) algorithm is a newly developed global meta-heuristic algorithm. It is efficient and easy to implement,  requiring no parameter tuning apart from the population size and the maximum number of iterations. Recently, WFS has been developed based on applying t-way strategies, where t represents the interaction strength. Despite the encouraging results, WFS's search strategy leans more toward local optima due to the narrowing of the boundary search space and the increased value of the search sharpness. Hybridising two or more algorithms enhances search performance by effectively balancing the strengths and mitigating the weaknesses of each method. Thus, this paper proposes a new hybrid Lévy Flight with Wingsuit Flying Search (WFS) algorithm called Enhanced Wingsuit Flying Search Algorithm (EWFS). EWFS uses a control mechanism to identify the best dynamic solution during runtime. The Lévy Flight motion helps the solution escape from local optima and improves the searching process when it gets stuck. Comparison between EWFS and WFS uses the benchmarking configuration of  CA(N; 2, 5⁷), while the comparison with other metaheuristic algorithms is based on the following covering array configurations: CA(N; t, 3p), CA(N; t, v7), CA(N; 2, 2p), and CA(N; t, 210). The experimental result shows that EWFS is statistically better regarding test suite size reduction than the recent t-way strategies. It also offers improved results of 65% over the original WFS and resolves the issues of excessive exploitation and getting stuck in local minima or maxima.

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Author Biographies

Nurol Husna Che Rose, Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia

Nurol Husna Che Rose is a PhD student in Computer Engineering at University Malaysia Perlis (UniMAP). Her research interests include software testing, optimization algorithms, and artificial intelligence. She is also a lecturer at UniMAP with nearly 5 years of teaching experience in software engineering field.

Rozmie Razif Othman, Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia

Assoc. Prof. Dr. Rozmie Razif Bin Othman obtained his bachelor’s degree in Electronics Engineering (Computer) from Multimedia University, Malaysia in 2006. Later in 2009, he finished his master’s degree in Telecommunication Engineering from University of Malaya. Then, he completed his doctoral degree in Software Engineering in 2012. His doctoral thesis is on the design and development of combinatorial test suite generator. His areas of interest are software testing, optimization algorithm and machine learning. He has produces more than 50 articles in his field of interest and graduated more than 5 post graduate students. He also a certified professional for Requirement Engineering (CPRE), Certified Tester for both Foundation Level (CTFL) and Advance Level (CTAL-TM). Currently, he is an Associate Professor of Computer Engineering in Universiti Malaysia Perlis (UniMAP).

Hasneeza Liza Zakaria, Advanced Computing, Centre of Excellence (CoE), Universiti Malaysia Perlis, Malaysia

Ts. Dr. Hasneeza Liza Zakaria earned her Ph.D. in Software Engineering from Universiti Malaysia Pahang (UMP). She also holds a Master’s degree in Computer Science from Universiti Teknologi Malaysia (UTM) and a Bachelor’s degree in Information Technology from Universiti Utara Malaysia (UUM). Her doctoral research centered on the development of a Hybrid Optimization Algorithm using the Etilist method. Her research interests span software testing, optimization algorithms, and other optimization problems. Additionally, she is a certified professional technologist with the Malaysia Board of Technologists (MBOT). Currently, she serves as a lecturer at UniMAP.

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Published
2025-12-10
How to Cite
Che Rose, N. H., Othman, R. R., Zakaria, H. L., Suali, A. J., Jamal Abdul Nasir, H., & Altmemi, J. (2025). Enhanced Wingsuit Flying Search (EWFS) Algorithm for Combinatorial T-way Test Suite Generation. EMITTER International Journal of Engineering Technology, 13(2), 229-252. https://doi.org/10.24003/emitter.v13i2.979
Issue
Vol 13 No 2 (2025)
Section
Articles

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