Artificial Bee Colony Algorithm for Pairwise Test Generation

Authors

  • Ammar K. Alazzawi Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Kuantan, Pahang, Malaysia.
  • Ameen A. Ba Homaid Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Kuantan, Pahang, Malaysia.
  • Alaa A. Alomoush Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Kuantan, Pahang, Malaysia.
  • AbdulRahman A. Alsewari Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Kuantan, Pahang, Malaysia. IBM Centre of Excellence.

Keywords:

Interation Testing, Test Data Generation, T-way Testing, Software Testing, Natural Based Search Algorithms, Optimization Problems,

Abstract

Our dependence on software applications has become dramatic in many activities of our daily life as they help to increase the efficiency of our tasks. These software applications have many sets of input values, parameters, software/hardware environments and system conditions, which need to be tested to ensure software reliability and quality. However, the whole comprehensive software testing is virtually not possible due to marketing pressure and resource constraints. In an attempt to solve this problem, there has been a development of a number of sampling and pairwise strategies in the literature. In this paper, we evaluated and proposed a pairwise strategy named Pairwise Artificial Bee Colony algorithm (PABC). According to the benchmarking results, the PABC strategies outdo some existing strategies to generate a test case in many of the system configurations taken into consideration. In a case where PABC is not at its optimal stage or its best performance, the experiments of a test case are effectively competitive. PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.

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Published

2017-03-01

How to Cite

K. Alazzawi, A., Ba Homaid, A. A., A. Alomoush, A., & A. Alsewari, A. (2017). Artificial Bee Colony Algorithm for Pairwise Test Generation. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(1-2), 103–108. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1666

Issue

Vol. 9 No. 1-2: Advancing Digital Societies for Social and Cultural Improvement

Section

Articles

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