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

Snehlata Sheoran, Neetu Mittal, Alexander Gelbukh

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

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.

Original languageEnglish
Pages (from-to)340-349
Number of pages10
JournalInternational Journal of Systems Assurance Engineering and Management
Volume11
Issue number2
DOIs
StatePublished - 1 Apr 2020

Keywords

  • Artificial Bee Colony (ABC)
  • Artificial intelligence
  • Data flow testing
  • Swarm intelligence
  • Test suite optimization

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