Resumo

TIMANA-PENA, Jimena Adriana; COBOS-LOZADA, Carlos Alberto  e  TORRES-JIMENEZ, Jose. Metaheuristic algorithms for building Covering Arrays: A review. Rev. Fac. ing. [online]. 2016, vol.25, n.43, pp.31-45. ISSN 0121-1129.

Covering Arrays (CA) are mathematical objects used in the functional testing of software components. They enable the testing of all interactions of a given size of input parameters in a procedure, function, or logical unit in general, using the minimum number of test cases. Building CA is a complex task that involves lengthy execution times and high computational loads. The most effective methods for building CAs are algebraic, Greedy, and metaheuristic-based. The latter have reported the best results to date. This paper presents a description of the major contributions made by a selection of different metaheuristics, including simulated annealing, tabu search, genetic algorithms, ant colony algorithms, particle swarm algorithms, and harmony search algorithms. It is worth noting that simulated annealing-based algorithms have evolved as the most competitive, and currently form the state of the art.

Palavras-chave : ant colony optimization; Covering Array; genetic algorithms; harmony search algorithm; metaheuristics; particle swarm optimization; simulated annealing; tabu search.

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