Products of mixed covering arrays of strength two

Colbourn, Charles J.; Martirosyan, Sosina; Mullen, Gary L.; Shasha, Dennis; Sherwood, George B.; Yucas, Joseph L.

doi:10.1002/jcd.20065

Cited by 107 publications

(73 citation statements)

References 25 publications

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“…There are four parameters and each one has two values that are represented in nine rows. A mixed level covering array (MCA) denoted by (n, t, k, (v 1 , ..., v k )) is also an n*k array in which the entries of the ith column arise from an alphabet of size v i ; in addition, choosing any t distinct columns i 1 , ..., i t , every t-tuple containing, for 1 ≤ j ≤ t, one of the v i j entries of column i j , appears in columns i 1 , ..., i t , in at least one of the N rows Colbourn et al (2006). …”

Section: Covering Arraymentioning

confidence: 99%

Test Algebra for Concurrent Combinatorial Testing

Tsai

2017

Combinatorial Testing in Cloud Computing

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A new algebraic system, Test Algebra (TA), is proposed for identifying faults in combinatorial testing for SaaS (Software-as-a-Service) applications. In the context of cloud computing, SaaS is a new software delivery model, in which mission-critical applications are composed, deployed, and executed on cloud platforms. Testing SaaS applications is challenging because new applications need to be tested once they are composed, and prior to their deployment. A composition of components providing services yields a configuration providing a SaaS application. While individual components in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty.When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 ≤ t ≤ k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.

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Section: Covering Arraymentioning

confidence: 99%

Test Algebra for Concurrent Combinatorial Testing

Tsai

2017

Combinatorial Testing in Cloud Computing

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“…Moura et al (2003) introduced a set of recursive algorithms for constructing CAs based on CAs of small sizes. Some recursive methods are product constructions (Colbourn & Ling, 2009;Colbourn et al, 2006;Martirosyan & Colbourn, 2005). Colbourn & Torres-Jimenez (2010) presented a recursive method to construct CAs using perfect hash families for CAs contruction.…”

Section: Relevant Related Workmentioning

confidence: 99%

Using Grid Computing for Constructing Ternary Covering Arrays

Ávila-George¹,

Torres-Jiménez²,

Carrión³

et al. 2012

Grid Computing - Technology and Applications, Widespread Coverage and New Horizons

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“…For t = 2 the best available Roux-type constructions appear in [21]; for t = 3 in [22]; for t = 4 in [22,53], and for t ≥ 5 in [52,53]. The basic strategy in each is to form a number of copies of a t-covering array on k factors to form an array on k factors, simply juxtaposing the copies.…”

Section: Combinatorial Constructionsmentioning

confidence: 99%

Locating and detecting arrays for interaction faults

2007

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The identification of interaction faults in component-based systems has focussed on indicating the presence of faults, rather than their location and magnitude. While this is a valuable step in screening a system for interaction faults prior to its release, it provides little information to assist in the correction of such faults. Consequently tests to reveal the location of interaction faults are of interest. The problem of nonadaptive location of interaction faults is formalized under the hypothesis that the system contains (at most) some number d of faults, each involving (at most) some number t of interacting factors. Restrictions on the number and size of the putative faults lead to numerous variants of the basic problem. The relationships between this class of problems and interaction testing using covering arrays to indicate the presence of faults, designed experiments to measure and model faults, and combinatorial group testing to locate faults in a more general testing scenario, are all examined. While each has some definite similarities with the fault location problems for componentbased systems, each has some striking differences as well. In this paper, we formulate the combinatorial problems for locating and detecting arrays to undertake interaction fault location. Necessary conditions for existence are established, and using a close connection to covering arrays, asymptotic bounds on the size of minimal locating and detecting arrays are established.

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Products of mixed covering arrays of strength two

Cited by 107 publications

References 25 publications

Test Algebra for Concurrent Combinatorial Testing

Test Algebra for Concurrent Combinatorial Testing

Using Grid Computing for Constructing Ternary Covering Arrays

Locating and detecting arrays for interaction faults

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