A tool for constrained pairwise test case generation using statistical user profile based prioritization

Nakornburi, Sompong; Suwannasart, Taratip

doi:10.1109/jcsse.2016.7748881

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…Given an invalid test case, a straightforward approach of replacing it is to clone this test case. In each clone, the parameters involved in constraints are changed to new values that do not violate constraints, and the number of clones is chosen to preserve coverage [6], [40], [84], [85], [86]. Another attempt is to first remove invalid test cases and then use a genetic algorithm to add some feasible ones [83].…”

Section: Replacementioning

confidence: 99%

A Survey of Constrained Combinatorial Testing

Wu¹,

Nie²,

Petke³

et al. 2019

Preprint

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Combinatorial Testing (CT) is a potentially powerful testing technique, whereas its failure revealing ability might be dramatically reduced if it fails to handle constraints in an adequate and efficient manner. To ensure the wider applicability of CT in the presence of constrained problem domains, large and diverse efforts have been invested towards the techniques and applications of constrained combinatorial testing. In this paper, we provide a comprehensive survey of representations, influences, and techniques that pertain to constraints in CT, covering 129 papers published between 1987 and 2018. This survey not only categorises the various constraint handling techniques, but also reviews comparatively less well-studied, yet potentially important, constraint identification and maintenance techniques. Since real-world programs are usually constrained, this survey can be of interest to researchers and practitioners who are looking to use and study constrained combinatorial testing techniques.

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Section: Replacementioning

confidence: 99%

A Survey of Constrained Combinatorial Testing

Wu¹,

Nie²,

Petke³

et al. 2019

Preprint

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“…In software testing, some combinations between input parameters and parameter values are commonly infeasible and unachievable in practice for executing in the SUT which will yield expensively false positives. Moreover, the pairwise testing technique does not provide a solution for handling the constraints between input parameters and parameter values, the testers have to review the test cases from pairwise testing and delete invalid test cases manually themselves [19]. For example from Table 1, consider that Internet Explorer cannot be executed on Mac OS so the operating system must not be Mac OS.…”

Section: Constraint Handlingmentioning

confidence: 99%

“…Constraints can be set as a form of logical expressions and rules. The logical expression and rules define a condition that must be achieved by every test case and must be performed correctness checking during test case generation whether a combination of identified parameters and parameter values or a test case violates the constraints or not [3,4,23]. The form of logical expression and rule can be converted from one to another as shown in Table 2.…”

Section: Constraints Modelingmentioning

confidence: 99%

“…Recent researchers suggest that a particular one of the widely practical used combinatorial testing technique is pairwise testing, it grew into extensive use and has been proved a useful technique for software testing and fault detection [3,4]. In addition, using a combinatorial testing technique not only detect more defects but also reduces time for designing test cases for a specific system under test (SUT) and significant cost and resources savings [5].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a user profile was found and used to indicate the frequency of a software system execution. By applying statistical user profile, a goal-oriented testing that has been found the most ideal approach that would help us to prioritize testing effort related to the actual usage of the software system and how often of the software system is being used [4,8,9]. As a result, we can dispose of each individual tester skills.…”

Section: Introductionmentioning

confidence: 99%

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Input Modeling Prioritization Using Statistically User Profile for Pairwise Test Case Generation with Constraints Handling

Nakornburi¹,

Suwannasart²

2017

Self Cite

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Abstract. Pairwise testing is a widely used technique for software testing with the reduced size of the test suite and able to detect interactions that trigger the system's faults. In addition, pairwise testing test suites must be able to take constraints between input parameters and parameter values into account. In current practice, identifying and selecting input parameters and parameter values usually depends on tester skills that might not be sufficient. Input parameters and parameter values modeling and tools for easily guiding and prioritizing the selection of optimal input parameters and parameter values for the SUT is also required. In this work, we present an approach for prioritizing input parameters and parameter values modeling using statistical user profile. Our approach is implemented in a tool called UPPTCT which provides the ability to handle constraints on input parameters and parameter values for pairwise testing in order to generate test cases. We conduct experiments to evaluate test case effectiveness and compare our tool with other renowned pairwise test generation and constraints handling tools. The experimental results show that the effectiveness of our approach is significantly more efficient and effective than random testing as a large portion of reported defects with regard to statically user profile were caught by our approach. Furthermore, our tool performs better in some cases and performs comparable results for generating test cases upon input parameters and parameter values for both with constraints handling and without constraints handling.

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