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Bug Localization Based on Code Change Histories and Bug Reports

机译:基于代码更改历史记录和错误报告的错误本地化

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A bug report is mainly used to find a fault location in software maintenance. It contains several fields such as summary, description, status and version. The description field includes detail scenario and stack traces if exceptional messages are presented. Recently researchers have proposed several approaches for automatic bug localization by using information retrieval and data mining. We propose BLIA, a statically integrated analysis approach of IR-based bug localization by utilizing texts and stack traces in bug reports, structured information of source files, and source code change histories. We performed experiments on three open source projects, namely AspectJ, SWT and ZXing. Compared with prior tools, our experiment results showed that BLIA outperforms the existing tools in terms of mean average precision. Our approach on average improved the metric of BugLocator, BLUiR, BRTracer and AmaLgam by 34%, 23%, 17% and 8%, respectively.
机译:错误报告主要用于在软件维护中找到故障位置。它包含几个字段,如摘要,描述,状态和版本。如果出现了异常消息,则说明字段包括详细信息方案和堆栈跟踪。最近,研究人员通过使用信息检索和数据挖掘提出了几种自动错误定位方法。我们提出了基于IR的错误本地化的静态综合分析方法,利用错误报告,结构化信息的源文件的结构化信息和源代码更改历史。我们对三个开源项目进行了实验,即AspectJ,SWT和ZXing。与现有工具相比,我们的实验结果表明,Blia在平均精度方面优于现有工具。我们平均地改善了34%,23%,17%和8%的34%,23%,17%和8%的灌注器,Bluir,Bluir,Bltracer和Amalgam的指标。

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