Implementation of Sand cat Swarm Optimization for Uniform T-Way Test Suite Generation

Muhammad Aiman bin Mohd Asyraf; Rozmie Razif Bin Othman; Mohd Zamri Bin Zahir Ahmad; Ahmad Ashraf Abdul Halim; Kentaro Go; Nuraminah binti Ramli; R. Badlishah Ahmad; Latifah Munirah Kamarudin; Murad Muhammad Hasan Salih Al-Walidi

doi:10.14313/jamris-2026-028

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Implementation of Sand cat Swarm Optimization for Uniform T-Way Test Suite Generation

Journal of Automation, Mobile Robotics and Intelligent Systems

Volume 20 (2026): Issue 2 (June 2026)

By: Muhammad Aiman bin Mohd Asyraf , Rozmie Razif Bin Othman , Mohd Zamri Bin Zahir Ahmad , Ahmad Ashraf Abdul Halim , Kentaro Go , Nuraminah binti Ramli , R. Badlishah Ahmad , Latifah Munirah Kamarudin and Murad Muhammad Hasan Salih Al-Walidi

Open Access

|Jun 2026

Figures & Tables

List of generated test cases for exhaustive testing

Test case generation for t = 2 and list of test cases for t-way

Pseudocode for Sand Cat Swarm Optimization Algorithm

Wilcoxon and Friedman Test for Group 2 and Group 3

No.	Paired Strategy	Test Statistic							Null Hypothesis	Conclusion
		Comparison for SCSO			Total Samples	p-value (Asymp. Sig. (2-tailed))	Friedman Mean Rank Test
		<	=	>			Mean Rank	Rank
1	SCSO vs Improved PSO	4	2	4	10	0.944	SCSO – 2.00	2	retain	no significant difference
							PSO – 1.85	1
2	SCSO vs TConfig	1	1	8		0.086	SCSO – 2.00	2	retain	no significant difference
							TConfig – 3.75	4
3	SCSO vs SITG	3	1	6		0.513	SCSO – 2.00	2	retain	no significant difference
							SITG – 2.50	3
4	SCSO vs IPOG	0	0	10		0.005	SCSO – 2.00	2	reject	SCSO outperforms
							IPOG – 4.90	5
5	SCSO vs ABCVS	1	1	3	5	0.715	SCSO – 1.70	2	retain	no significant difference
							ABCVS – 1.30	1

Wilcoxon and Friedman Test for Group 1 and Group 2

No.	Paired Strategy	Test Statistic							Null Hypothesis	Conclusion
		Comparison for SCSO			Total Samples	p -value (Asymp. Sig. (2-tailed))	Friedman Mean Rank Test
		<	=	>			Mean Rank	Rank
1.	SCSO vs ACOF	18	4	3	25	0.002	SCSO – 5.76	7	reject	ACOF outperforms
							ACOF – 3.32	2
2.	SCSO vs TTSGA	19	3	3		0.002	SCSO – 5.76	7	reject	TTSGA outperforms
							TTSGA – 3.88	3
3.	SCSO vs HHH	18	2	5		0.01	SCSO – 5.76	7	reject	HHH outperforms
							HHH – 2.84	1
4.	SCSO vs HSS	19	1	5		0.005	SCSO – 5.76	7	reject	HSS outperforms
							HSS – 3.92	4
5.	SCSO vs PSTG	16	4	5		0.055	SCSO – 5.76	7	retain	no significant difference
							PSTG – 4.86	6
6.	SCSO vs CS	17	2	6		0.083	SCSO – 5.76	7	retain	no significant difference
							CS – 4.16	5
7.	SCSO vs TVG	0	4	21		0.001	SCSO – 5.76	7	reject	SCSO outperforms
							TVG – 7.92	8
8.	SCSO vs IPOG	2	0	23		0.001	SCSO – 5.76	7	reject	SCSO outperforms
							IPOG – 8.34	9
9.	SCSO vs WFS	8	6	8	22	0.532	SCSO – 2.27	3
							WFS – 2.23	2	retain	no significant difference
10.	SCSO vs GSTG	14	6	2		0.013	SCSO – 2.27	3	reject	GSTG outperforms
							GSTG – 1.50	1
11.	SCSO vs TConfig	14	3	5	22	0.099	SCSO – 1.30	1	retain	no significant difference
							TConfig – 1.70	2
12.	SCSO vs WOA	16	1	0	17	0.001	SCSO – 1.97	2	reject	WOA outperforms
							WOA – 1.03	1
13.	SCSO vs QLSCA	8	2	2	12	0.012	SCSO – 2.50	3	reject	QLSCA outperforms
							QLSCA – 1.63	1
14.	SCSO vs ATBLO	8	2	2		0.012	SCSO – 2.50	3	reject	ATBLO outperforms
							ATBLO – 1.88	2

Result Test Suite Size Performance for Group 1

CA(t,v⁷)		Metaheuristic-based Strategies												Computational-based Strategies
t	v	2026	2024	2023	2022	2020	2019	2018	2017	2016	2011	2010	2009	2010	2007	1990s
		SCSO	WFS	ACOF	GSTG	WOA	TTSGA	QLSCA	ATLBO	HHH	HSS	PSTG	CS	TVG	IPOG	TConfig
2	2	7	7	6	6	6	7	7	7	7	7	6	6	7	8	7
	3	15	15	15	15	14	15	15	15	14	14	15	15	15	17	15
	4	26	27	26	26	25	25	23	23	23	25	26	25	27	28	28
	5	40	40	37	40	36	38	34	34	35	35	37	37	42	42	40
3	2	14	13	12	12	12	12	15	15	15	12	13	12	15	19	16
	3	51	51	48	49	49	49	49	49	49	50	50	49	55	57	55
	4	124	123	117	121	116	118	112	111	112	121	116	117	134	208	112
	5	240	242	230	240	223	228	215	216	216	223	225	223	260	275	239
4	2	30	25	30	26	27	29	31	31	31	29	29	27	31	48	36
	3	158	156	148	155	152	152	149	151	148	155	155	155	167	185	166
	4	497	513	485	499	484	485	477	480	482	500	487	487	559	509	568
	5	1220	X	1174	1217	NA	1175	1150	1166	1153	1174	1176	1171	1385	1349	1320
5	2	52	51	53	52	52	55	X	X	58	53	53	53	59	128	56
	3	434	442	430	430	432	433	X	X	435	437	441	439	464	608	477
	4	1833	1861	1825	1822	1815	1821	X	X	1805	1831	1826	1845	2010	2560	1792
	5	5535	X	5450	X	X	5457	X	X	5413	5468	5474	5479	6257	8091	X
6	2	70	66	64	64	64	68	X	X	64	64	64	66	78	64	64
	3	949	955	970	971	945	957	X	X	853	916	977	973	1016	1281	921
	4	5621	5610	5450	5611	5567	5487	X	X	5478	4096	5599	5610	5978	4096	X
	5	21580	X	21145	X	X	21148	X	X	21107	21748	21595	21597	23218	28513	X
*Total*	0	2	6	4	4	0	5	3	8	4	2	2	0	2	2
*Optimal*	0%	*10%*	*30%*	*20%*	*20%*	0%	*25%*	*15%*	*40%*	*20%*	*10%*	*10%*	0%	*10%*	*10%*

Result Test Suite Size Performance for Group 3

CA(t, 3⁷)	Metaheuristic-based Strategies				Computational-based Strategies
	2026	2022	2019	2015	2007	1990s
t	SCSO	Improved PSO	ABCVS	SITG	IPOG	TConflg
2	15	15	15	15	17	15
3	51	45	49	52	57	55
4	158	152	157	154	185	166
5	434	444	442	436	608	477
6	949	832	944	848	1281	921
*Total*	2	4	1	1	0	1
*Optimal*	*40%*	*80%*	*20%*	*20%*	0%	*20%*

Result Test Suite Size Performance for Group 2

CA(t, 2¹⁰)	Metaheuristic-based Strategies											Computational-based Strategies
	2026	2024	2023	2022	2022	2019	2016	2015	2011	2010	2009	2010	2007	1990s
t	SCSO	WFS	ACOF	GSTG	ImprovedPSO	TTSGA	HHH	SITG	HSS	PSTG	CS	TVG	IPOG	TConfig
2	8	8	8	8	9	8	8	9	7	8	8	10	10	9
3	17	16	16	16	16	16	16	16	16	17	16	17	19	20
4	34	38	39	27	39	36	36	44	37	37	36	41	49	45
5	84	84	74	74	84	76	79	87	81	82	79	84	128	95
6	159	160	153	156	168	155	153	174	158	158	157	168	352	183
*Total*	0	1	3	3	1	1	2	1	2	0	1	0	0	0
*Optimal*	0%	*20%*	*60%*	*60%*	*20%*	*20%*	*40%*	*20%*	*40%*	0%	*20%*	0%	0%	0%

Classification Representation of Input Parameters

Input parameter	U	L	D	M	C
Possible Value	U1	L1	D1	M1	C1
	U2	L2	D2	M2	C2
		L3		M3

References

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.14313/jamris-2026-028 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649

Journal RSS Feed

Language: English

Page range: 144 - 159

Submitted on: Jun 10, 2025

Accepted on: Nov 24, 2025

Published on: Jun 24, 2026

Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

T-way combinatorial testing,

test suite generation,

sand cat swarm optimization (SCSO),

metaheuristic algorithm

Related subjects:

Computer sciences,

Artificial intelligence,

Engineering,

Electrical engineering,

Control engineering, metrology and testing,

Mechanical engineering,

Fundamentals of mechanical engineering

© 2026 Muhammad Aiman bin Mohd Asyraf, Rozmie Razif Bin Othman, Mohd Zamri Bin Zahir Ahmad, Ahmad Ashraf Abdul Halim, Kentaro Go, Nuraminah binti Ramli, R. Badlishah Ahmad, Latifah Munirah Kamarudin, Murad Muhammad Hasan Salih Al-Walidi, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 20 (2026): Issue 2 (June 2026)

Implementation of Sand cat Swarm Optimization for Uniform T-Way Test Suite Generation

Figures & Tables

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Wilcoxon and Friedman Test for Group 2 and Group 3

Wilcoxon and Friedman Test for Group 1 and Group 2

Result Test Suite Size Performance for Group 1

Result Test Suite Size Performance for Group 3

Result Test Suite Size Performance for Group 2

Classification Representation of Input Parameters

Paradigm

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