Improving Failure Detection by Automatically Generating Test Cases Near the Boundaries
Sponsor
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.
Published In
Computer Software and Applications Conference (COMPSAC), 2016 IEEE 40th Annual
Document Type
Citation
Publication Date
8-25-2016
Abstract
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.
Locate the Document
DOI
10.1109/COMPSAC.2016.137
Persistent Identifier
http://archives.pdx.edu/ds/psu/20215
Citation Details
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.