Abstract
A lot of test cases need to be executed in statistical software testing. A test case consists of a set of inputs and a list of expected outputs. To automatically generate the expected outputs for a lot of test cases is rather difficult. An attribute reduction based approach is proposed in this paper to automatically generate the expected outputs. In this approach the input and output variables of a software are expressed as conditional attributes and decision attributes respectively. The relationship between input and output variables are then obtained by attribute reduction. Thus, the expected outputs for a lot of test sets are automatically generated via the relationship. Finally, a case study and the comparison results are presented, which show that the method is effective.
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Ye, M., Feng, B., Zhu, L., Lin, Y. (2006). Attribute Reduction Based Expected Outputs Generation for Statistical Software Testing. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_114
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DOI: https://doi.org/10.1007/11795131_114
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36297-5
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