Journal of Software:2021.32(2):247-276

(计算机软件新技术国家重点实验室(南京大学), 江苏 南京 210023;计算机软件新技术国家重点实验室(南京大学), 江苏 南京 210023;南通大学 信息科学技术学院, 江苏 南通 226019)
Survey on Information Retrieval-based Software Bug Localization Methods
LI Zheng-Liang,CHEN Xiang,JIANG Zhi-Wei,GU Qing
(State Key Laboratory for Novel Software Technology(Nanjing University), Nanjing 210023, China;State Key Laboratory for Novel Software Technology(Nanjing University), Nanjing 210023, China;School of Information Science and Technology, Nantong University, Nantong 226019, China)
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Received:January 16, 2020    Revised:July 05, 2020
> 中文摘要: 基于信息检索的软件缺陷定位方法是当前软件缺陷定位领域中的一个研究热点.该方法主要分析缺陷报告文本和程序模块代码,通过计算缺陷报告和程序模块间的相似度,选取与缺陷报告相似度最高的若干程序模块,将其推荐给开发人员.对近些年国内外研究人员在该综述主题上取得的成果进行了系统的梳理和总结.首先,给出研究框架并阐述影响方法性能的3个重要因素——数据源、检索模型和场景应用;其次,依次对这3个影响因素的已有研究成果进行总结;然后,总结基于信息检索的软件缺陷定位研究中常用的性能评测指标和评测数据集;最后总结全文,并对未来值得关注的研究方向进行展望.
Abstract:Information retrieval-based software bug localization is an active research topic in the domain of software fault localization. It first analyzes the contents of the bug reports and program modules. Then it calculates the similarity between the bug reports and program modules. Finally, it recommends the most similar program modules to developers when given a bug report. This paper presents a systematic survey of existing research achievements of the domestic and international researchers in recent years. First, a research framework is proposed and three key factors (i.e., data sources, retrieval model, and application scenario), which may influence the performance of bug localization methods are identified. Next, existing research achievements in these three key factors are discussed in sequence. Then, the performance evaluation measures and datasets commonly used in information retrieval-based bug localization are summarized. Finally, conclusions of this study are drawn and a perspective of the future work in this research area is discussed.
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基金项目:国家自然科学基金(61972192,61202006,61906085,41972111);第2次青藏高原综合科学考察研究项目(2019QZKK0204);南京大学计算机软件新技术国家重点实验室开放课题(KFKT2019B14,KFKT2018B17) 国家自然科学基金(61972192,61202006,61906085,41972111);第2次青藏高原综合科学考察研究项目(2019QZKK0204);南京大学计算机软件新技术国家重点实验室开放课题(KFKT2019B14,KFKT2018B17)
Foundation items:National Natural Science Foundation of China (61972192, 61202006, 61906085, 41972111); Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0204); Open Project of State Key Laboratory for Novel Software Technology at Nanjing University (KFKT2019B14, KFKT2018B17)
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LI Zheng-Liang,CHEN Xiang,JIANG Zhi-Wei,GU Qing.Survey on Information Retrieval-based Software Bug Localization Methods.Journal of Software,2021,32(2):247-276