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

被引：13
|
作者：
Sheoran, Snehlata [1 ]
Mittal, Neetu [1 ]
Gelbukh, Alexander [2 ]
机构：
[1] Amity Univ Uttar Pradesh, Noida, Uttar Pradesh, India
[2] Inst Politecn Nacl IPN, Mexico City, DF, Mexico
来源：
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT | 2020年 / 11卷 / 02期
关键词：
Swarm intelligence; Data flow testing; Artificial intelligence; Test suite optimization; Artificial Bee Colony (ABC); OPTIMIZATION;
D O I：
10.1007/s13198-019-00862-1
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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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页码：340 / 349
页数：10
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