Test Design as Code: JCUnit

Ukai, Hiroshi; Qu, Xiao

doi:10.1109/icst.2017.58

Cited by 3 publications

(3 citation statements)

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“…Given that both ACTS and PICT have their own limitations in constraint definition, we introduced a new tool in our previous work Ukai (2007) .…”

Section: Background and Related Workmentioning

confidence: 99%

“…Minimizing changes is important because the output, which represents a test suite, sometimes contains fundamental parameters that are expensive to control such as OS or filesystem to be used in test execution. Popular tools for CIT such as ACTS ( Kuhn, Kacker & Lei, 2008 ), PICT ( Czerwonka, 2006 ), and JCUnit ( Ukai 2007 ) can add parameters not presented in an initial covering array and generate an output as by assigning values to them so that the combinations between the values of the given parameters and the existing ones are covered. However, this limits reuse of only one covering array.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Such a capability is provided only by limited tools. Various tools, which generate covering arrays of a specified strength under constraints, have been developed and proposed, such as ACTS ( Kuhn, Kacker & Lei, 2008 ), PICT ( Czerwonka, 2006 ), JCUnit ( Ukai 2007 ), etc. , each of which has its own strengths and weaknesses.…”

Section: Introductionmentioning

confidence: 99%

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Accelerating covering array generation by combinatorial join for industry scale software testing

Ukai

Qu²,

Washizaki

et al. 2022

PeerJ Computer Science

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Combinatorial interaction testing, which is a technique to verify a system with numerous input parameters, employs a mathematical object called a covering array as a test input. This technique generates a limited number of test cases while guaranteeing a given combinatorial coverage. Although this area has been studied extensively, handling constraints among input parameters remains a major challenge, which may significantly increase the cost to generate covering arrays. In this work, we propose a mathematical operation, called “weaken-product based combinatorial join”, which constructs a new covering array from two existing covering arrays. The operation reuses existing covering arrays to save computational resource by increasing parallelism during generation without losing combinatorial coverage of the original arrays. Our proposed method significantly reduce the covering array generation time by 13–96% depending on use case scenarios.

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“…Given that both ACTS and PICT have their own limitations in constraint definition, we introduced a new tool in our previous work Ukai (2007) .…”

Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%