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| 基于信息检索的软件缺陷定位技术研究进展 |
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张芸1, 刘佳琨2, 夏鑫3, 吴明晖1, 颜晖1
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1.浙江大学城市学院 计算机与计算科学学院, 浙江 杭州 310015;2.浙江大学 计算机科学与技术学院, 浙江 杭州 310007;3.Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia
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| 摘要: |
| 缺陷定位是软件工程研究最活跃的领域之一.大部分软件缺陷都会被提交到类似于Bugzilla和Jira的缺陷追踪系统中.由于提交的缺陷报告数量过多，开发人员不能及时处理，因而迫切需要一个自动化工具来帮助开发人员识别缺陷相关源代码文件.研究人员已提出了大量缺陷定位技术.基于信息检索的软件缺陷定位技术（information retrieval-based bug localization，简称IRBL）利用了缺陷报告的文本特性，并且由于计算成本低、对不同的程序语言更具普适性而成为缺陷定位领域的研究热点，取得了一系列研究成果.然而，IRBL技术也在数据预处理、相似度计算和工程应用等方面存在诸多挑战.鉴于此，对现有的IRBL技术进行梳理总结，主要内容包括：（1）梳理了IRBL中数据预处理的过程和信息检索通用方法；（2）对IRBL技术中利用的数据特征进行了详细的分类和总结；（3）总结了技术评估中使用的性能评估指标；（4）归纳出了IRBL技术的关键问题；（5）展望了IRBL技术的未来发展. |
| 关键词: 缺陷报告定位 信息检索 软件工程 |
| DOI：10.13328/j.cnki.jos.006081 |
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| 基金项目:2019年度高层次留学回国人员在杭创新项目 |
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| Research Progress on Software Bug Localization Technology Based on Information Retrieval |
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ZHANG Yun1, LIU Jia-Kun2, XIA Xin3, WU Ming-Hui1, YAN Hui1
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1.School of Computer and Computing Science, Zhejiang University City College, Hangzhou 310015, China;2.College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China;3.Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia
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| Abstract: |
| Bug localization is one of the most active domains in software engineering. Most of the bugs are submitted to bug tracker systems, e.g., Bugzilla and Jira. Because of the large number of the submitted bug reports, it is difficult for developers to resolve these defects in time. Therefore, an automatic tool to help developers to identify bug related files is needed. Many bug localization technologies have been proposed by researchers. Taking advantages of the text nature of bug report, information retrieval technologies are adopted to solve bug localization problems. Due to the low computing cost and the applicability to various programming languages, information retrieval-based bug localization (IRBL) technologies become hot spots in bug localization and acquire a series of achievements. However, challenges still exist in data preprocessing, similarity calculation, and engineering application. Therefore, current IRBL technologies are summarized. The contributions of this study are: (1) the data preprocess methods and general information retrieval algorithms are summarized; (2) the feature categories are concluded and classified; (3) the performance measures are concluded; (4) the current problems in IRBL technologies are highlighted; and (5) the trends of IRBL technologies are outlooked. |
| Key words: bug report localization information retrieval software engineering |
