Title

Computational Intelligence for Functional Testing

Document Type

Book Chapter

Publisher

IGI Global

Faculty

Computing, Health and Science

School

Computer & Security Science

RAS ID

8841

Comments

This chapter was originally published as: Lam, C. P. (2010). Computational Intelligence for Functional Testing. In F.Meziane and S. Vadera (Eds.). Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects (pp. 233- 258). Location: IGI Global. Original book available here

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 10 generation of test scenarios. Owing to its anti-ant behaviour, the approach generates non-redundant test scenarios.

DOI

10.4018/978-1-60566-758-4.chOI2

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Link to publisher version (DOI)

10.4018/978-1-60566-758-4.chOI2