Abstract
The development of a new software system involves extensive tests on the software functionality in order to identify possible failures. It will be ideal to test all possible input cases (configurations), but the exhaustive approach usually demands too large cost and time. The test suite reduction problem can be defined as the task of generating small set of test cases under certain requirements. A way to design test suites is through interaction testing using a matrix called Covering Array, CA(N;t,k,v), which guarantees that all configurations among every t parameters are covered. This paper presents a simple strategy that reduces the number of rows of a CA. The algorithms represent a post-optimization process which detects wild cards (values that can be changed arbitrarily without the CA losses its degree of coverage) and uses them to merge rows. In the experiment, 667 CAs, created by a state-of-the-art algorithm, were subject to the reduction process. The results report a reduction in the size of 347 CAs (52% of the cases). As part of these results, we report the matrix for CA(42;2,8,6) constructed from CA(57;2,8,6) with an impressive reduction of 15 rows, which is the best upper bound so far.
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Gonzalez-Hernandez, L., Torres-Jimenez, J., Rangel-Valdez, N., Bracho-Rios, J. (2013). A Post-optimization Strategy for Combinatorial Testing: Test Suite Reduction through the Identification of Wild Cards and Merge of Rows. In: Batyrshin, I., Mendoza, M.G. (eds) Advances in Computational Intelligence. MICAI 2012. Lecture Notes in Computer Science(), vol 7630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37798-3_12
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DOI: https://doi.org/10.1007/978-3-642-37798-3_12
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