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CLC number: TP311

On-line Access: 2017-03-10

Received: 2015-11-01

Revision Accepted: 2016-03-20

Crosschecked: 2017-02-28

Cited: 0

Clicked: 3753

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Deng Chen

http://orcid.org/0000-0001-6359-801X

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Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.3 P.332-345

http://doi.org/10.1631/FITEE.1500379


Efficient vulnerability detection based on an optimized rule-checking static analysis technique


Author(s):  Deng Chen, Yan-duo Zhang, Wei Wei, Shi-xun Wang, Ru-bing Huang, Xiao-lin Li, Bin-bin Qu, Sheng Jiang

Affiliation(s):  Hubei Provincial Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China; more

Corresponding email(s):   chendeng8899@hust.edu.cn

Key Words:  Rule-based static analysis, Software quality, Software validation, Performance improvement


Deng Chen, Yan-duo Zhang, Wei Wei, Shi-xun Wang, Ru-bing Huang, Xiao-lin Li, Bin-bin Qu, Sheng Jiang. Efficient vulnerability detection based on an optimized rule-checking static analysis technique[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 332-345.

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author="Deng Chen, Yan-duo Zhang, Wei Wei, Shi-xun Wang, Ru-bing Huang, Xiao-lin Li, Bin-bin Qu, Sheng Jiang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="3",
pages="332-345",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500379"
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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.

基于改进规则检查静态分析技术的高效脆弱性检测方法

概要:静态分析是保障软件开发质量的一种重要方法。通过与软件开发过程集成并进行交互式应用可进一步提升静态分析工具的作用优势。然而,静态分析工具的交互式应用具有高性能和快速响应等要求。为此,本文以基于规则检查技术的静态分析工具作为研究对象,提出一种改进的规则检查算法,旨在提升静态分析工具的性能。该方法首先采用一种领域描述语言构造脆弱性规则的特征对象表达式,然后基于特征对象表达式的运算结果,对脆弱性规则进行过滤。由于一个代码文件通常只包含与部分脆弱性规则相关的错误,通过规则过滤可有效提高规则检查算法的效率,进而提升静态分析的性能。为了对方法可行性及有效性进行评估,方法实现过程被集成到开源静态分析工具PMD中并基于扩展后的PMD进行了实验分析。实验结果表明提出的方法可在不损失静态分析检测能力和精度的情况下获得平均28.7%的性能提升。

关键词:基于规则的静态分析技术;软件质量;软件验证;性能改进

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