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T-Tuple Reallocation: An Algorithm to Create Mixed-Level Covering Arrays to Support Software Test Case Generation

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Abstract

A fact that is known both by researchers and by industry professionals is that exhaustive software testing is impractical. Therefore, one of the most studied activities of software testing process is the generation/selection of test cases. However, selecting test cases that reveal the greatest number of defects within a software is a challenging task, due to the significantly high amount of entries that the system can receive, and even due to the different characteristics of software products in several application domains. This work presents a new algorithm, called T-Tuple Reallocation (TTR), to generate Mixed-Level Covering Array (MCA) which is one of the techniques of combinatorial designs that aims at test case generation. After studying various algorithms/techniques to generate combinatorial designs, starting with pairwise design, TTR was proposed aiming at decreasing the amount of test cases produced to test a software product. The new algorithm was able to create shorter sets of test cases in comparison with classical algorithms/tools proposed in the literature. Although TTR, in general, demanded longer time to generate the sets of test cases, this rise in time can be compensated by a smaller number of test cases so that less time is required for executing them. In the end, this may imply less time for accomplishing the testing process as a whole.

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Correspondence to Juliana Marino Balera .

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Balera, J.M., de Santiago Júnior, V.A. (2015). T-Tuple Reallocation: An Algorithm to Create Mixed-Level Covering Arrays to Support Software Test Case Generation. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9158. Springer, Cham. https://doi.org/10.1007/978-3-319-21410-8_39

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  • DOI: https://doi.org/10.1007/978-3-319-21410-8_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21409-2

  • Online ISBN: 978-3-319-21410-8

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