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Artificial bee colony algorithm in data flow testing for optimal test suite generation

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Abstract

Meta-heuristic Artificial Bee Colony Algorithm finds its applications in the optimization of numerical problems. The intelligent searching behaviour of honey bees forms the base of this algorithm. The Artificial Bee Colony Algorithm is responsible for performing a global search along with a local search. One of the major usage areas of Artificial Bee Colony Algorithm is software testing, such as in structural testing and test suite optimization. The implementation of Artificial Bee Colony Algorithm in the field of data flow testing is still unexplored. In data flow testing, the definition-use paths which are not definition-clear paths are the potential trouble spots. The main aim of this paper is to present a simple and novel algorithm by making use of artificial bee colony algorithm in the field of data flow testing to find out and prioritize the definition-use paths which are not definition-clear paths.

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Authors and Affiliations

  1. Amity University Uttar Pradesh, Noida, Uttar Pradesh, India

    Snehlata Sheoran & Neetu Mittal

  2. Instituto Politécnico Nacional [IPN], Mexico City, Mexico

    Alexander Gelbukh

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  1. Snehlata Sheoran
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  2. Neetu Mittal
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  3. Alexander Gelbukh
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Correspondence to Snehlata Sheoran.

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Sheoran, S., Mittal, N. & Gelbukh, A. Artificial bee colony algorithm in data flow testing for optimal test suite generation. Int J Syst Assur Eng Manag 11, 340–349 (2020). https://doi.org/10.1007/s13198-019-00862-1

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