基于优化的Co-Trade软件故障定位方法  

Software Fault Localization Method Based on Optimizing Co-Trade

作　　者：李勇[1] LI Yong(School of Computer Science and Engineering , Chang chun University of Technology , Chang chun 710054,China)

机构地区：[1]长春工业大学计算机科学与工程学院,吉林长春130012

出　　处：《内蒙古师范大学学报（自然科学汉文版）》2017年第2期278-281,共4页Journal of Inner Mongolia Normal University(Natural Science Edition)

基　　金：吉林省教育厅"十二五"科学技术研究规划资助项目

摘　　要：传统的软件故障定位方法样本需求量大、费用昂贵.针对这一问题,提出了一种优化的Co-Trade软件故障定位方法.首先,利用执行语句与测试语句之间的动态关系实现协同学习,在语句级利用半监督方法训练分类器;然后,对Co-Trade算法的权值进行自适应优化,进一步改善分类器的性能,并对后续执行语句进行判别式分类,从而定位故障信息;最后,基于Siemens Suite数据库对算法的性能进行了计算机仿真分析.经对比分析,该方法具有较强的有效性和优越性.Traditional software fault location method need large sample and expensive.In order to solve this problem,this paper proposes a software fault localization method based on optimizing Co-Trade.First,the method realizes collaborative learning using the dynamic relationship between the statement and testing execution.And the classifier is trained using semi-supervised method in the statement level.Second,this paper optimize the Co-Trade weights and improves the performance of the classifier.The method discriminates the subsequent statement execution and locates the fault information.Finally,computer simulation is conducted based on the Siemens Suite database,and the results are compared with several existing methods,which show that the proposed method is superiority.

关 键 词：软件故障 协同训练 分类器 训练样本 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]