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Computational Intelligence for Functional Testing

Computational Intelligence for Functional Testing
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Author(s): C. Peng Lam (Edith Cowan University, Australia)
Copyright: 2012
Pages: 24
Source title: Machine Learning: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-818-7.ch502

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Abstract

Software testing is primarily a technique for achieving some degree of software quality and to gain consumer confidence. It accounts for 50% -75% of development cost. Test case design supports effective testing but is still a human centered and labour-intensive task. The Unified Modelling language (UML) is the de-facto industrial standard for specifying software system and techniques for automatic test case generation from UML models are very much needed. While extensive research has explored the use of meta-heuristics in structural testing, few have involved its use in functional testing, particularly with respect to UML. This chapter details an approach that incorporates an anti-Ant Colony Optimisation algorithm for the automatic generation of test scenarios directly from UML Activity Diagrams, thus providing a seamless progression from design to generation of test scenarios. Owing to its anti-ant behaviour, the approach generates non-redundant test scenarios.

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