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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/3607
- Title
- Good random testing
- Author(s)
- Chan, Kwok P.; Chen, Tsong Y.; Towey, David
- Abstract
- Software Testing is recognized as an essential part of the Software Development process. Random Testing (RT), the selection of test cases at random from the input domain, is a simple and efficient method of Software Testing. Previous research has indicated that, under certain circumstances, the performance of RT can be improved by enforcing a more even, well-spread distribution of test cases over the input domain. Test cases that contribute to this goal can be considered good, and are more desirable when choosing potential test cases than those that do not contribute. Fuzzy Set Theory enables a calculation of the degree of membership of the set of good test cases for any potential test case, in other words, a calculation of how good the test case is. This paper presents research in the area of improving on the failure finding efficiency of RT using Fuzzy Set Theory. An approach is proposed and evaluated according to simulation results and comparison with other testing methods.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies
- Source
- Paper presented to the 9th Ada-Europe International Conference on Reliable Software Technologies, Vol. 3063 (2004), pp. 200-212
- Publication year
- 2004
- Publisher
- Springer-Verlag
- Format
- pp. 200-212
- Publisher URL
- http://dx.doi.org/10.1007/b97913
- Copyright
- Copyright 2004
- Peer reviewed
