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.
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Chan, K.P., Chen, T.Y., Towey, D. (2004). Good Random Testing. In: Llamosí, A., Strohmeier, A. (eds) Reliable Software Technologies - Ada-Europe 2004. Ada-Europe 2004. Lecture Notes in Computer Science, vol 3063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24841-5_16
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DOI: https://doi.org/10.1007/978-3-540-24841-5_16
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