期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：24
页码：6996
出版社：Journal of Theoretical and Applied
摘要：Software is the inseparable part of todays human life. Each and every gadget that we use is dependent on some or other kind of software. Component based software engineering (CBSE) has provided an effective software development paradigm which allows selection of domain specific components from component repository and assemble them into a modular and scalable application. The reliability of software and its components depends on the amount of effective testing carried on it during its development life cycle. We cannot deny the fact that exhaustive testing is not possible. Selection of appropriate test suite is a combinatorial problem. Soft computing provides a promising solution for the same. Emergence of artificial intelligence over years has added fuel to nature inspired testing techniques. This paper is a comparative study of various soft computing approaches inspired by nature for reusable software components such as artificial neural network, genetic algorithm, fuzzy logic and other swarm based techniques. A comparative analysis is presented to discuss pros and cons of different soft computing techniques for software testing of reusable components along with their preferences in recent years. A future dimension is also proposed to develop hybrid techniques for optimization of testing techniques.
关键词：Soft computing; Test Case Prioritization; Testing; Reusable Components.
