Title

Computational Intelligence for Functional Testing

Document Type

Book Chapter

Publisher

IGI Global

Faculty

Faculty of Computing, Health and Science

School

School of Computer and 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

 
COinS
 

Link to publisher version (DOI)

10.4018/978-1-60566-758-4