利用信息检索和代码克隆定位技术扩展Bug定位

Matthew D. Beard
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引用次数: 2

摘要

缺陷定位包括使用有关缺陷的信息来帮助定位必须修改以修复缺陷的代码部分。这样的任务可能涉及软件开发人员和/或维护人员的大量时间和精力。近年来,一些基于信息检索(IR)模型的自动化缺陷定位技术得到了发展,以加快缺陷定位的进程。另一种代码分析技术涉及在软件项目中定位重复的代码部分,称为代码克隆。我们研究了代码克隆定位技术在bug定位中的应用。我们试图通过在分析过程中包含IR模型来确定扩展现有代码克隆定位技术的优势。我们还研究了一种扩展bug日志存储库和版本控制系统使用的技术,方法是使用IR技术对两者进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending Bug Localization Using Information Retrieval and Code Clone Location Techniques
Bug localization involves the use of information about a bug to assist in locating sections of code that must be modified to fix the bug. Such a task can involve a considerable amount of time and effort on the part of software developers and/or maintainers. Recently, several automated bug localization techniques based on information retrieval (IR) models have been developed to speed the process of bug localization. Another code analysis technique involves locating duplicated sections of code in software projects, called code clones. We examine the application of code clone location techniques in the context of bug localization. We attempt to determine the advantages of extending existing code clone location techniques through the inclusion of IR models in the analysis process. We also examine a technique for extending the use of bug logging repositories and version control systems by analyzing the two using IR techniques.
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