Metaheuristic algorithms for building Covering Arrays: A review

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...

সম্পূর্ণ বিবরণ

গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক: Timaná-Peña, Jimena Adriana, Cobos-Lozada, Carlos Alberto, Torres-Jimenez, Jose
বিন্যাস: Online
ভাষা:eng
প্রকাশিত: Universidad Pedagógica y Tecnológica de Colombia 2016
বিষয়গুলি:
অনলাইন ব্যবহার করুন:https://revistas.uptc.edu.co/index.php/ingenieria/article/view/5295
বিবরন
সংক্ষিপ্ত: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 (NP-complete problem) 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.