Improving Failure Detection by Automatically Generating Test Cases Near the Boundaries
This research is sponsored in part by NSFC Program (No. 91218302, 61402248), and MIIT IT funds (Research and application of TCN key technologies) of China.
Computer Software and Applications Conference (COMPSAC), 2016 IEEE 40th Annual
Boundary value analysis is a typical conventional testing technique. However, manually identifying input regions and writing test cases are labor-intensive and time-consuming. In this paper, we propose a search-based random testing approach, which automatically generates test data along the boundaries of semantic regions of the input domain. The experiments on mutated programs confirm the effectiveness and efficiency of the proposed approach. Furthermore, our approach significantly outperforms the conventional ART (Adaptive Random Testing) methods, which sample test cases evenly across the input regions. Our approach also outperforms EvoSuite, a state-of-the-art tool that generates test cases satisfying certain coverage criterion.
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M. Zhou, X. Cheng, X. Guo, M. Gu, H. Zhang and X. Song, "Improving Failure Detection by Automatically Generating Test Cases Near the Boundaries," 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC), Atlanta, GA, 2016, pp. 164-173.