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Optimization Driven Constraints Handling in Combinatorial Interaction Testing

Optimization Driven Constraints Handling in Combinatorial Interaction Testing

Ram Gouda, Chandraprakash V.
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 19
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781522565543|DOI: 10.4018/IJOSSP.2019070102
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MLA

Gouda, Ram, and Chandraprakash V. "Optimization Driven Constraints Handling in Combinatorial Interaction Testing." IJOSSP vol.10, no.3 2019: pp.19-37. http://doi.org/10.4018/IJOSSP.2019070102

APA

Gouda, R. & Chandraprakash V. (2019). Optimization Driven Constraints Handling in Combinatorial Interaction Testing. International Journal of Open Source Software and Processes (IJOSSP), 10(3), 19-37. http://doi.org/10.4018/IJOSSP.2019070102

Chicago

Gouda, Ram, and Chandraprakash V. "Optimization Driven Constraints Handling in Combinatorial Interaction Testing," International Journal of Open Source Software and Processes (IJOSSP) 10, no.3: 19-37. http://doi.org/10.4018/IJOSSP.2019070102

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Abstract

The combinatorial strategy is useful in the reduction of the number of input parameters into a compact set of a system based on the combinations of the parameters. This strategy can be used in testing the behaviour that takes place when the events are allowed to be executed in an appropriate order. Basically, in the software systems, for the highly configurable system, the input configurations are based on the constraints, and the construction of this idea undergoes various kinds of difficulties. The proposed Jaya-Bat optimization algorithm is developed with the combinatorial interaction test cases in an effective manner in the presence of the constraints. The proposed Jaya-Bat based optimization algorithm is the integration of the Jaya optimization algorithm (JOA) and the Bat optimization algorithm (BA). The experimentation is carried out in terms of average size and the average time to prove the effectiveness of the proposed algorithm. From the results, it is clear that the proposed algorithm is capable of selecting the test cases optimally with better performance.

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