[1]杨振兴,刘久富,孙 琳.不变量的程序潜在错误预测[J].智能系统学报,2010,5(4):327-331.
YANG Zhen-xing,LIU Jiu-fu,SUN Lin.Using invariants to predict the potential for errors in programs[J].CAAI Transactions on Intelligent Systems,2010,5(4):327-331.
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YANG Zhen-xing,LIU Jiu-fu,SUN Lin.Using invariants to predict the potential for errors in programs[J].CAAI Transactions on Intelligent Systems,2010,5(4):327-331.
不变量的程序潜在错误预测
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
5
期数:
2010年第4期
页码:
327-331
栏目:
学术论文—人工智能基础
出版日期:
2010-08-25
- Title:
- Using invariants to predict the potential for errors in programs
- 文章编号:
- 1673-4785(2010)04-0327-05
- Keywords:
- invariants; software testing; support vector machine; error prediction
- 分类号:
- TP311
- 文献标志码:
- A
- 摘要:
- 随着软件系统变得越来越复杂和庞大，软件中的安全缺陷也急剧增加，系统中的隐含错误也在逐渐增多.提出一种基于不变量的程序潜在错误预测方法，首先采用支持向量机对程序属性所产生的非函数依赖程序不变量进行学习并产生机器学习模式，然后运用该机器学习模式对需预测的程序进行属性分类，并揭示出代码可能存在的潜在错误，最后通过实验验证该方法是有效的.
- Abstract:
- As software systems become increasingly complex and large, deficiencies in software security increase sharply and implicit errors increase gradually. A method based on invariants was developed to predict potential errors in programs. First, a support vector machine was used to find program invariants and produce a pattern for machine learning. Then the pattern from machine learning was employed to classify the programs with behavior to be predicted and reveal the latent errors in codes. Finally an experiment was done that verified the effectiveness of the method.
- 参考文献/References:
-
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?［2］BRUN Y. Software fault identification via dynamic analysis and machine learning［D］. Cambridge Massachusetts Institute of Technology, 2003.
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WANG Tinghua, TIAN Shengfeng, HUANG Houkuan. Feature weighted support vector machine［J］. Journal of Electronics & Information Technology ,2009, 31(3)： 514-518.
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［5］李嘉.基于支持向量机的软件可靠性早期预测研究［D］.合肥:合肥工业大学, 2005.
?LI Jia. The study of software reliability early prediction based on support vector machine［D］. Hefei: Heifei University of Technology, 2005.
［6］刘杰,阳小华,罗扬，等. 一种交互式的不变量动态发现编配工具［J］.计算机应用与软件，2008,10：85-86.
?LIU Jie, YANG Xiaohua, LUO Yang, et al. An interacten instrum enter for dynamically discovering invariant［J］. Computer Applications and Software, 2008, 10： 85-86.
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备注/Memo
收稿日期：2009-10-12.
基金项目：国家自然科学基金资助项目（60674100).
通信作者：杨振兴.-mail：yzxwfu@163.com.
作者简介：杨振兴，男，1985年生，硕士研究生，主要研究方向为软件测试与人工智能.
更新日期/Last Update:
2010-09-20