Non-specification-based approaches to logic testing for software

Kobayashi, Noritaka; Tsuchiya, Tatsuhiro; Kikuno, Tohru

doi:10.1016/s0950-5849(01)00222-1

Cited by 44 publications

(40 citation statements)

References 23 publications

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“…Weyuker et al [23] dealt with the constraints in two ways: ignoring and including them as conjoints. The specifications and therefore the same approach was taken by Chen et al to introduce the testing criterion MUMCUT [2], by Kobayashi et al [18] for evaluating the combinatorial and random/anti-random approaches to test generation, and by [15] to evaluate the Minimal-MUMCUT strategy. We found no testing criterion or technique that explicitly implements the third (VAL) approach for Boolean specifications.…”

Section: Methodsmentioning

confidence: 99%

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Dealing with Constraints in Boolean Expression Testing

Gargantini

2011

2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops

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Abstract-When testing a Boolean expression, one should consider also the constraints among the variables contained in it. Constraints model interdependence among the conditions in the expressions. Only tests that satisfy the constraints. i.e. valid tests, are really useful and can be applied to test the expression. We present three ways to deal with such constraints: (1) ignoring them during test generation and removing invalid tests later, (2) including them in the expression as conjoint and again removing invalid tests later, and (3) considering them during the test generation process in order to generate only valid tests from the start. We introduce a general framework in which the three policies are implemented and compared over a set of Boolean expressions commonly used as benchmarks. Although the third policy requires a constraints solving technique for actual test generation, it presents several benefits: it generates smaller test suites and it may require less time for tests generation. Moreover, ignoring the constraints during test generation can reduce the fault detection capability of the tests.

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Section: Methodsmentioning

confidence: 99%

“…IGN and INC policies are commonly used in test generation for Boolean expressions [8], [23], [2], [18]. The VAL policy has never been applied to logic testing, but it is commonly used with test generation for programs using constraint solving techniques [11].…”

Section: Example 2 Given the Following C Code Fragmentmentioning

confidence: 99%

Dealing with Constraints in Boolean Expression Testing

Gargantini

2011

2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops

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“…There are five major studies: [15] which addressed coverage, [16], [17], [18]and [19] which addressed effectiveness at detecting seeded faults.…”

Section: Combinatorial Techniquesmentioning

confidence: 99%

The Effectiveness of T-Way Test Data Generation

Ellims¹,

Ince

Petre

Lecture Notes in Computer Science

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Abstract. This paper reports the results of a study comparing the effectiveness of automatically generated tests constructed using random and t-way combinatorial techniques on safety related industrial code using mutation adequacy criteria. A reference point is provided by hand generated test vectors constructed during development to establish minimum acceptance criteria. The study shows that 2-way testing is not adequate measured by mutants kill rate compared with hand generated test set of similar size, but that higher factor t-way test sets can perform at least as well. To reduce the computation overhead of testing large numbers of vectors over large numbers of mutants a staged optimising approach to applying t-way tests is proposed and evaluated which shows improvements in execution time and final test set size.

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“…Seroussi and Bshouty [15] showed that the problem of computing the least sized CIT test suite for twise coverage of a given system is NP-complete. Despite exact solutions to compute it by algebraic construction do exist [8], in fact these are not generally applicable to all systems. As a consequence, researchers have addressed the issue of designing generally applicable algorithms, based on greedy heuristics, although these may lead to sub-optimal results (typically, only an upper bound on the size of the constructed suite may be guaranteed).…”

Section: Introductionmentioning

confidence: 99%

Building T-wise Combinatorial Interaction Test Suites by Means of Grid Computing

Calvagna

Gargantini

Tramontana

2009

2009 18th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises

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Generally, systematic testing is the only way to assess the occurrence of failures in systems consisting in a set of components, however given the size of real-world systems, it would be very expensive to construct and test all the possible combinations of the states of components. Combinatorial interaction testing is an existing tecnique that appropriately reduces the number of test cases by choosing either pairs, triplets, etc., i.e. t-tuples, of input values. Of course, the effectiveness of a test suite is higher when choosing e.g. triplets of inputs rather than pairs. Since high values of t are preferable, a large number of test cases could still be generated.This paper proposes a technique for building the smallest possible test suite of size t. This technique consists in reducing the number of test cases by carefully choosing non redundant t-tuples. The paper shows that for obtaining the smallest possible set of tests, it is best to generate a large 'flexible' set of t-tuples and then reduce such a set until the smallest one is obtained. Reduction is a computationally expensive operation and therefore it is worth performing it by parallelising its execution. This paper proposes a solution for executing the reduction algorithm over a set of Grid resources.

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Non-specification-based approaches to logic testing for software

Cited by 44 publications

References 23 publications

Dealing with Constraints in Boolean Expression Testing

Dealing with Constraints in Boolean Expression Testing

The Effectiveness of T-Way Test Data Generation

Building T-wise Combinatorial Interaction Test Suites by Means of Grid Computing

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