An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite

Abdullah, Nasser and Kamal Z., Zamli and Alsewari, Abdulrahman A. and Ahmed, Bestoun S. (2018) An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite. International Journal of Bio-Inspired Computation, 12 (2). pp. 115-127. ISSN 1758-0366. (Published)

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In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). Although useful, most of the aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive system, such an assumption is invalid as some parameter operations (or events) occur in sequence and hence, creating a possibility of bugs triggered by the order (or sequence) of input parameters. If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. In line with such a need, this paper presents a unified strategy based on the new meta-heuristic algorithm, called the elitist flower pollination algorithm (eFPA), for sequence and sequence-less coverage. Experimental results demonstrate the proposed strategy gives sufficiently competitive results as compared with existing works.

Item Type: Article
Uncontrolled Keywords: T-way testing; flower pollination algorithm; event sequence testing; combinatorial problem; meta-heuristics; optimisation problem.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Prof. Dr. Kamal Zuhairi Zamli
Date Deposited: 30 Jan 2019 04:24
Last Modified: 30 Jan 2019 04:24
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