Affiliation:
1. School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China
2. Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Jiangsu University Zhenjiang China
Abstract
SummaryCombinatorial testing (CT) is considered as a practical approach to detect software faults, which has arisen from the interaction between factors affecting the software behavior. However, most of the traditional algorithms on CT generation did not take advantage of the execution results of the earlier test cases, as well as neglect the impact of the nonequilibrium input parameter model (NE‐IPM) effect on redundant test cases, which bring a deleterious effect to the detection accuracy of the software faults. To solve these problems, we propose a novel CT approach with fuzzing strategy called CTAF. Based on the idea that fuzzing is performed during execution, CTAF exploits the execution results of earlier tests to provide guidance for subsequent test generation thereby reducing the redundant test cases without compromising the diversity of test cases. And then, we designed three experiments on real subjects of six open source software systems, and the experimental results show that the proposed CTAF approach can effectively improve the NE‐IPM effect and enhance the detection accuracy of software faults.
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China
Natural Science Foundation of Jiangsu Province
China Postdoctoral Science Foundation
Graduate Research and Innovation Projects of Jiangsu Province