General Application of a Decision Support Framework for Software Testing Using Artificial Intelligence Techniques
The use of artificial intelligent (AI) techniques for testing software applications has been investigated for over a decade. This paper proposes a framework to assist test managers to evaluate the use of AI techniques as a potential tool to test software. The framework is designed to facilitate decision making and provoke the decision maker into a better understanding of the use of AI techniques as a testing tool. We provide an overview of the framework and its components. Fuzzy Cognitive Maps (FCMs) are employed to evaluate the framework and make decision analysis easier, and therefore help the decision making process about the use of AI techniques to test software. What-if analysis is used to explore and illustrate the general application of the framework.
KeywordsTest Environment Software Test Test Manager Artificial Intelligent Technique Result Vector
Unable to display preview. Download preview PDF.
- 1.Dick, S., Kandel, A.: Computational intelligence in software quality assurance. Series in machine perception and artificial intelligence, vol. 63. World Scientific, Hackensack (2005)Google Scholar
- 3.Institute of Electrical and Electronics Engineers. IEEE standard for software test documentation. USA (IEEE Std. 829-1983) (1983) Google Scholar
- 4.Institute of Electrical and Electronics Engineers. IEEE standard glossary of software engineering terminology. USA (IEEE Std. 610.12-1990) (1990) Google Scholar
- 5.Patton, R.: Software testing, 2nd edn. Sams Publishing, Indiana (2006)Google Scholar
- 6.Dustin, E., Rashka, J., Paul, J.: Automated software testing: Introduction, management, and performance. Addison-Wesley, Reading (1999)Google Scholar
- 7.Harman, M., McMinn, P.: A theoretical & empirical analysis of evolutionary testing and hill climbing for structural test data generation. In: Proceedings of the 2007 International Symposium on Software Testing and Analysis, pp. 73–83 (2007)Google Scholar
- 8.Hermadi, I., Ahmed, M.A.: Genetic algorithm based test data generator. In: The 2003 Congress on Evolutionary Computation, vol. 1, pp. 85–91 (2003)Google Scholar
- 14.Tian, J.: Software quality engineering: Testing, quality assurance, and quantifiable improvement. Wiley, Hoboken (2005)Google Scholar