| Regular Papers |
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| Efficient vulnerability detection based on an optimized rule-checking static analysis technique |
| Deng Chen, Yan-duo Zhang, Wei Wei, Shi-xun Wang, Ru-bing Huang, Xiao-lin Li, Bin-bin Qu, Sheng Jiang |
| Hubei Provincial Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China; Industrial Robot Engineering Center, Wuhan Institute of Technology, Wuhan 430205, China; School of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China; School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang 212013, China; School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China |
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Abstract Static analysis is an efficient approach for software assurance. It is indicated that its most effective usage is to perform analysis in an interactive way through the software development process, which has a high performance requirement. This paper concentrates on rule-based static analysis tools and proposes an optimized rule-checking algorithm. Our technique improves the performance of static analysis tools by filtering vulnerability rules in terms of characteristic objects before checking source files. Since a source file always contains vulnerabilities of a small part of rules rather than all, our approach may achieve better performance. To investigate our technique’s feasibility and effectiveness, we implemented it in an open source static analysis tool called PMD and used it to conduct experiments. Experimental results show that our approach can obtain an average performance promotion of 28.7% compared with the original PMD. While our approach is effective and precise in detecting vulnerabilities, there is no side effect.
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Received: 01 November 2015
Published: 10 March 2017
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