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Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites

Kamal Z., Zamli and Fakhrud, Din and Salmi, Baharom and Ahmed, Bestoun S. (2017) Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites. Engineering Applications of Artificial Intelligence, 59. pp. 35-50. ISSN 0952-1976

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Abstract

The teaching learning-based optimization (TLBO) algorithm has shown competitive performance in solving numerous real-world optimization problems. Nevertheless, this algorithm requires better control for exploitation and exploration to prevent premature convergence (i.e., trapped in local optima), as well as enhance solution diversity. Thus, this paper proposes a new TLBO variant based on Mamdani fuzzy inference system, called ATLBO, to permit adaptive selection of its global and local search operations. In order to assess its performances, we adopt ATLBO for the mixed strength t-way test generation problem. Experimental results reveal that ATLBO exhibits competitive performances against the original TLBO and other meta-heuristic counterparts.

Item Type: Article
Uncontrolled Keywords: Software testing; t-way testing; Teaching learning-based optimization algorithm; Mamdani fuzzy inference system
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Centre of Excellence: IBM Centre of Excellence
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 16 Jun 2017 03:31
Last Modified: 16 Jan 2018 00:48
URI: http://umpir.ump.edu.my/id/eprint/16453
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