Greedy Heuristic Algorithms to Generate Variable Strength Combinatorial Test Suite

Wang, Ziyuan; Xu, Bin; Nie, Changhai

doi:10.1109/qsic.2008.52

Cited by 54 publications

(38 citation statements)

References 6 publications

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“…Heuristic based OTAT strategy uses a heuristic method in deciding the final test data. Density (Wang et al, 2008), simulated annealing (SA) (Cohen et al, 2003) and automatic efficient test generator (AETG) (Cohen et al, 1994) are the strategies that can be characterized as heuristic based OTAT strategy. Density used the global and local density calculation (extension of "density" concept introduced by Colbourn (2009, 2007) for constructing the final test data.…”

Section: Related Workmentioning

confidence: 99%

“…Density used the global and local density calculation (extension of "density" concept introduced by Colbourn (2009, 2007) for constructing the final test data. Formulae to calculate both global and local density can be found in Wang et al (2008). As for SA, the strategy starts with constructing a feasible solution and the applying a series of transformation to the solution until the solution cover all generated pairs.…”

Section: Related Workmentioning

confidence: 99%

“…Since there are varying supports as far as interaction strength is concerned (that is, some strategies deal with only small interaction strength), we have decided to perform two different experiments based on the benchmark configurations in Wang et al (2008) and Klaib (2009). The first experiment adopts lower interaction strength (that is, t = 3) while the second experiment used Table 3.…”

Section: Ittdg As Uniform Strength T-way Strategymentioning

confidence: 99%

“…Not until recently, a number of such strategies have started to appear (for example, Density (Wang et al, 2008), ParaOrder (Wang et al, 2007) and TVG (Arshem, 2010). However, as t-way test data generation is NP hard problem (Klaib, 2009;Cohen et al, 1997), no single existing strategy can claim dominance as far optimality of test size is concerned.…”

Section: Introductionmentioning

confidence: 99%

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ITTDG: Integrated T-way test data generation strategy for interaction testing

Othman¹,

Zamli²

2011

Sci. Res. Essays

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In the last 20 years, software has grown tremendously in terms of size (that is, line of codes (LOCs), and functionalities). With the increase in LOCs and functionalities, more and more unwanted interactions amongst software systems, hardware components, and operating systems are to be expected, rendering increased possibility of faults. While traditional static and dynamic testing strategies are useful for fault detection and prevention, they may not be sufficient to tackle bugs due to interaction. This paper describes the development of an integrated t-way test data generation (ITTDG) strategy for interaction testing (where t indicates the interaction strength). Unlike most existing works, ITTDGseamlessly integrates all forms of interaction possibilities including uniform, variable strength, and input output based relationship. Empirical evidence demonstrates that, ITTDG produces competitive test size as compared to existing strategies on a number of benchmark configurations.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Ittdg As Uniform Strength T-way Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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ITTDG: Integrated T-way test data generation strategy for interaction testing

Othman¹,

Zamli²

2011

Sci. Res. Essays

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“…Recently, researchers have also started to adopt meta-heuristics based strategies including that of Genetic Algorithm (GA) GA (Sthamer 1995;Shiba, Tsuchiya et al 2004;Bryce and Colbourn 2007;Afzal, Torkar et al 2009;Chen, Gu et al 2009;McCaffrey 2010), Ant Colony (ACS) ACA (Harman and Jones 2001;Shiba, Tsuchiya et al 2004;Wang, Xu et al 2008;Afzal, Torkar et al 2009;Chen, Gu et al 2009), Particle Swarm Optimization (PSTG) PSTG Ahmed and Zamli 2011;Ahmed, Zamli et al 2012), and Harmony Search Strategy (HSS) (Alsewari and Zamli 2012). Although these aforementioned strategies are useful, many of them fall short in term of the support for constraints (i.e.…”

Section: Introductionmentioning

confidence: 99%

Comparative Benchmarking of Constraints T-Way Test Generation Strategy Based on Late Acceptance Hill Climbing Algorithm

Zamli¹,

Alsewari²,

Alkazemi³

2015

ijsecs

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This paper describes the new t-way strategy based the Late Acceptance based Hill Climbing algorithm, called LAHC, for constraints t-way test generation. Unlike earlier competing work, LAHC does not require significant tuning in order to have it working. In fact, LAHC merely requires minor adjustment of the common controlling parameters involving iteration and population size depending on the given system configuration. Our benchmarking results have been promising as LAHC gives competitive results in most constraints configurations considered.

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Variable strength covering arrays

Raaphorst

Moura

Stevens

2018

J of Combinatorial Designs

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Recently, covering arrays have been the subject of considerable research attention as they hold both theoretical interest and practical importance due to their applications to testing. In this thesis, we perform the first comprehensive study of a generalization of covering arrays called variable strength covering arrays, where we dictate the interactions to be covered in the array by modeling them as facets of an abstract simplicial complex.We outline the necessary background in the theory of hypergraphs, combinatorial testing, and design theory that is relevant to the study of variable strength covering arrays. We then approach questions that arise in variable strength covering arrays in a number of ways. We demonstrate their connections to hypergraph homomorphisms, and explore the properties of a particular family of abstract simplicial complexes, the qualitative independence hypergraphs. These hypergraphs are tightly linked to variable strength covering arrays, and we determine and identify several of their important properties and subhypergraphs.We give a detailed study of constructions for variable strength covering arrays, and provide several operations and divide-and-conquer techniques that can be used in building them. In addition, we give a construction using linear feedback shift registers from primitive polynomials of degree 3 over arbitrary finite fields to find variable strength covering arrays, which we extend to strength-3 covering arrays whose sizes are smaller than many of the best known sizes of covering arrays.We then give an algorithm for creating variable strength covering arrays over arbitrary abstract simplicial complexes, which builds the arrays one row at a time, using a density concept to guarantee that the size of the resultant array is asymptotic in the logarithm of the number of facets in the abstact simplicial complex. This algorithm is of immediate practical importance, as it can be used to create test suites for combinatorial testing.Finally, we use the Lovász Local Lemma to nonconstructively determine upper bounds on the sizes of arrays for a number of different families of hypergraphs. We lay out a framework that can be used for many hypergraphs, and then discuss possible strategies that can be taken in asymmetric problems.ii Acknowledgements This thesis certainly could not have been completed without the help of many people.Firstly and most importantly, I would like to extend my immeasurable thanks to both of my supervisors, Lucia Moura and Brett Stevens. As a lowly undergraduate student many years ago, I had the extreme fortune of being chosen to serve as a teaching assistant to work with Lucia Moura. I could never have predicted that that was to be the first step on a long and rewarding journey into academia. Through all the opportunities she gave me, I caught her infectious enthusiasm for research and had my eyes opened to the wonderful fields of design theory and covering arrays. Without her endless patience and compassion with my quirkiness, this thesis would never...

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Greedy Heuristic Algorithms to Generate Variable Strength Combinatorial Test Suite

Cited by 54 publications

References 6 publications

ITTDG: Integrated T-way test data generation strategy for interaction testing

ITTDG: Integrated T-way test data generation strategy for interaction testing

Comparative Benchmarking of Constraints T-Way Test Generation Strategy Based on Late Acceptance Hill Climbing Algorithm

Variable strength covering arrays

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