[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,(04):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,(04):327-331.
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
期数:
2010年04期
页码:
327-331
栏目:
出版日期:
2010-08-25

文章信息/Info

Title:
Using invariants to predict the potential for errors in programs
文章编号:
1673-4785(2010)04-0327-05
作者:
杨振兴刘久富孙 琳
南京航空航天大学 自动化学院,江苏 南京210016
Author(s):
YANG Zhen-xing LIU Jiu-fu SUN Lin
College of Automation Engineering, Nanjing University of Areonautics and Astronautics, Nanjing 210016, China
关键词:
不变量软件测试支持向量机错误预测
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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备注/Memo

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