期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：4
页码：259-274
DOI：10.14569/IJACSA.2019.0100431
出版社：Science and Information Society (SAI)
摘要：To achieve acceptable quality and performance of any software product, it is crucial to assess various software components in the application. There exist various software-testing techniques such as combinatorial testing and covering array. However, problems such as t-way combinatorial explosion is still challenging in any combinatorial testing strategy, as it takes into consideration the entire combinations of input variables. Therefore, to overcome this problem, several optimizations and metaheuristic strategies have been suggested. One of the most effective optimization algorithms based techniques is the Artificial Bee Colony (ABC) algorithm. This paper presents t-way generation strategy for both a uniform and variable strength test suite by applying the ABC strategy (ABCVS) to reduce the size of the test suite and to subsequently enhance the test suite generation interaction. To assess both the effectiveness and performance of the presented ABCVS, several experiments were conducted applying various sets of benchmarks. The results revealed that the proposed ABCVS outweigh the existing based strategies and demonstrated wider interaction between components as opposed to AI-search based and computational based strategies. The results also revealed higher prospect of ABCVS in the aspect of its effectiveness and performance as observed in the majority of case studies.
关键词：T-way testing; variable-strength interaction; combinatorial testing; covering array; test suite generation; artificial bee colony algorithm
