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基于高斯过程的缺陷定位方法
引用本文:陈理国,刘超.基于高斯过程的缺陷定位方法[J].软件学报,2014,25(6):1169-1179.
作者姓名:陈理国  刘超
作者单位:北京航空航天大学计算机学院, 北京 100191;北京航空航天大学计算机学院, 北京 100191
基金项目:国家高技术研究发展计划(863)(2007AA010302)
摘    要:在软件系统中,缺陷定位是缺陷修复的一个关键环节,如果能将缺陷自动定位到很小的范围,将会极大地降低缺陷修复的难度.基于高斯过程提出了一种缺陷定位方法(GPBL),即针对每个缺陷,向开发人员推荐这个缺陷可能存在于哪些源文件中,从而帮助开发人员快速修复缺陷.为了验证方法的有效性,采集了开源软件Eclipse 和Argouml 中的数据,实验结果表明,高斯过程缺陷定位的查全率和查准率平均分别为87.16%和78.90%.与基于LDA的缺陷定位方法进行比较,表明高斯过程更能准确定位缺陷的位置.

关 键 词:缺陷定位  缺陷修复  缺陷报告  推荐方法  高斯过程
收稿时间:2012/11/16 0:00:00
修稿时间:2012/11/16 0:00:00

Bug Localization Method Based on Gaussian Processes
CHEN Li-Guo and LIU Chao.Bug Localization Method Based on Gaussian Processes[J].Journal of Software,2014,25(6):1169-1179.
Authors:CHEN Li-Guo and LIU Chao
Affiliation:School of Computer Science and Engineering, BeiHang University, Beijing 100191, China;School of Computer Science and Engineering, BeiHang University, Beijing 100191, China
Abstract:In software systems, bug localization is a key step in the bug fix process. By automatically narrowing down potential bug locations, the difficulty of bug fix is greatly reduced. In this paper, a bug localization method based on Gaussian processes, called Gaussian processes bug localization (GPBL) is proposed. This method can facilitate fixing bugs for the developers, by recommending source files that may contain bugs. In order to evaluate GPBL, the open-source software Eclipse and Argouml are employed as data sources. Experimental results show that GPBL can achieve 87.16% recall and 78.90% precision on average. In addition, GPBL can locate relevant buggy files more accurately compared with LDA-based bug localization methods.
Keywords:bug localization  bug fix  bug report  recommendation method  Gaussian processes
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