ABC Algorithm for Combinatorial Testing Problem

No default citation style available for Eprints

[img]
Preview
PDF
2877-7789-1-SM Alsewari MySec.pdf

Download (809kB) | Preview

Abstract

Computer software is in high demand everywhere in the world. The high dependence on software makes software requirements more complicated. As a result, software testing tasks get costlier and challenging due to a large number of test cases, coupled with the vast number of the system requirements. This challenge presents the need for reduction of the system redundant test cases. A combinatorial testing approach gives an intended result from the optimization of the system test cases. Hence, this study implements a combinatorial testing strategy called Artificial Bee Colony Test Generation (ABC-TG) that helps to get rid of some of the current combinatorial testing strategies. Results obtained from the ABC-TG were benchmarked with the results obtained from existing strategies in order to determine the efficiency of the ABC-TG. Finally, ABC-TG shows the efficiency and effectiveness in terms of generating optimum test cases size of some of the case studies and a comparable result with the existing combinatorial testing strategies.

Item Type: Article
Uncontrolled Keywords: Computational Intelligence; Combinatorial Optimization Problem; Software Testing; Test Data Generation
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Centre of Excellence: IBM Centre of Excellence
Faculty of Computer System And Software Engineering
Depositing User: Dr. AbdulRahman Ahmed Mohammed Al-Sewari
Date Deposited: 17 Nov 2017 02:53
Last Modified: 25 Sep 2018 08:39
URI: http://umpir.ump.edu.my/id/eprint/19042
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item