Abstract
Software systems have been increasingly used by our society, so a failure in them can lead to large losses. To reduce the failures of a software it is necessary to carry out the testing process appropriately. The combinatorial testing helps in the testing process by providing structures with a test set of small size, like Mixed Covering Arrays (MCAs). However, the problem of constructing an optimal test set is an NP-complete problem leading to the development of non exhaustive approaches to solve it. This paper proposes a new approach of Tabu Search (TS) called MiTS (that stands for Mixed Tabu Search) which focuses on constructing MCAs. The approach is based on the use of a mixture of neighborhood functions and a fine tuning process to improve the performance of the TS. Experimental evidence shows a poor performance when a single neighborhood function is used. In the other side, the TS (using a mixture of neighborhood functions) is competitive in the construction of MCAs over a known benchmark reported in the literature.
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Gonzalez-Hernandez, L., Torres-Jimenez, J. (2010). MiTS: A New Approach of Tabu Search for Constructing Mixed Covering Arrays. In: Sidorov, G., Hernández Aguirre, A., Reyes GarcÃa, C.A. (eds) Advances in Soft Computing. MICAI 2010. Lecture Notes in Computer Science(), vol 6438. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16773-7_33
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DOI: https://doi.org/10.1007/978-3-642-16773-7_33
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