A Bat-Inspired Testing Strategy for Generating Constraints Pairwise Test Suite

Alsariera, Yazan A.; Ahmed, Hussam; Alamri, Hammoudeh S.; Majid, Mazlina Abdul; Zamli, Kamal Z.

doi:10.1166/asl.2018.12922

Cited by 10 publications

(10 citation statements)

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“…Recently, researchers began focusing on meta-heuristic algorithms as a main algorithm for tway test set generation strategies such as Bat Algorithm (BA) [8][9][10][11][12][13], Hill Climbing (HC) [28], Simulated Annealing (SA) [27,28,31,41], Tabu Search (TS) [47,48], Artificial Bee Colony (ABC) [14][15][16], Particle Swarm Optimization (PSO) [49], Cuckoo Search (CS) [50], Ant Colony Algorithm (ACA) [51], Genetic Algorithm (GA) [52], Kidney Algorithm (KA) [18] and others. The most essential algorithm used for a 2-way test set generation ( also termed pairwise test set generation) is HC [28].…”

Section: Related Workmentioning

confidence: 99%

“…Recently, the efforts of researchers have been focused on metaheuristic algorithms as a foundation for t-way strategies. These include Bat Algorithm [8][9][10][11][12][13], Artificial Bee Colony [14][15][16][17] and Kidney Algorithm [18], to name just a few. However, it is impossible to find meta-heuristic algorithms to compensate for other existing algorithms for all optimization problems.…”

Section: Introductionmentioning

confidence: 99%

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HABCSm: A Hamming Based t-way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation

Alazzawi¹,

Rais²,

Basri³

et al. 2021

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Search-based software engineering that involves the deployment of meta-heuristics in applicable software processes has been gaining wide attention. Recently, researchers have been advocating the adoption of meta-heuristic algorithms for t-way testing strategies (where t points the interaction strength among parameters). Although helpful, no single meta-heuristic based t-way strategy can claim dominance over its counterparts. For this reason, the hybridization of meta-heuristic algorithms can help to ascertain the search capabilities of each by compensating for the limitations of one algorithm with the strength of others. Consequently, a new meta-heuristic based t-way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. HABCSm is the first t-way strategy to adopt Hybrid Artificial Bee Colony (HABC) algorithm with Hamming distance as its core method for generating a final test set and the first to adopt the Hamming distance as the final selection criterion for enhancing the exploration of new solutions. The experimental results demonstrate that HABCSm provides superior competitive performance over its counterparts. Therefore, this finding contributes to the field of software testing by minimizing the number of test cases required for test execution.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

HABCSm: A Hamming Based t-way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation

Alazzawi¹,

Rais²,

Basri³

et al. 2021

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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“…In 2012, Alsewari invented a HHS-based strategy or HS [24]. HSS imitating the conduct of musicians trying to compose extraordinary music from improvisations, such as modifying a memory melody or random sampling.…”

Section: Existing T-way Strategiesmentioning

confidence: 99%

Review of Combinatorial Testing Strategy

Altmemi¹

2019

IJATCSE

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Combinatorial testing (CT) is an essential technique that usually aims for the generation of test cases. The generation of an optimally sized test case is a Non-deterministic Polynomial (NP) problem. The Combinatorial Interaction has been discussed by several researchers in developing different strategies depending on support interactions. Combinatorial testing taxonomy is thus Suggested to facilitate the analysis. In this paper, 12 algorithms were evaluated based on the strategy approach, supported interactions, randomness, and publication year. The year 2011 was noted as the most successful year in which researchers generated t-way algorithms. For them, the one-test-per-time OTAT strategy was the most promising area for Combinatorial t-way analysis. A small variation was seen in the type of interaction support. Nonetheless, uniform strength was the most common form of interaction from the year 2010 to the first half of the year 2018. This article was therefore implemented to review existing t-way strategies to identify their capabilities and limitations, thus providing a valuable guideline for generating the future.

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“…The introduction of the bat-inspired testing strategy (BST) strategy aimed to support both pairwise testing and constraints [34]. It utilizes a one-test-at-a-time approach, creating test cases within the bat algorithm mechanism.…”

Section: Introductionmentioning

confidence: 99%

Pairwise test case generation with harmony search, one-parameter-at-at-time, seeding, and constraint mechanism integration

Aminu Muazu,

Hashim,

Maiwada

et al. 2024

IJECE

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Pairwise testing is a method for identifying defects through combinatorial analysis. It involves testing all possible combinations of input parameters in pairs within a system, ensuring that each pair is tested at least once. The field of test case generation is highly active in the realm of combinatorial interaction testing. Research in this area is particularly encouraged, as it falls under the category of non-deterministic polynomial-time hardness. A big challenge in this field is the combinatorial explosion problem. It is about finding the best test suite that covers all possible combinations of interaction strength. In this paper, we present the task of discovering a pairwise test set as a search problem and introduce an innovative testing tool referred to as pairwise test case generation in harmony search algorithm with seeding and constraint mechanism (PHOSC). Experimental results show that PHOSC performs better compared to some existing pairwise strategies in terms of test suite size. Additionally, PHOSC provides a comprehensive framework and serves as a research platform for the generation of pairwise test sets employing the harmony search algorithm. It adopts an approach that focuses on one parameter at a time (OPAT) and incorporates seeding and constraint mechanisms at the same time, thereby enhancing the efficiency and effectiveness of the testing process.

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A Bat-Inspired Testing Strategy for Generating Constraints Pairwise Test Suite

Cited by 10 publications

References 0 publications

HABCSm: A Hamming Based t-way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation

HABCSm: A Hamming Based t-way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation

Review of Combinatorial Testing Strategy

Pairwise test case generation with harmony search, one-parameter-at-at-time, seeding, and constraint mechanism integration

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