| 引用本文: | 郑炜,王晓龙,陈翔,夏鑫,廖慧玲,刘程远,孙瑞阳.重复软件缺陷报告检测方法综述.软件学报,2022,33(6):2288-2311 |
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| 重复软件缺陷报告检测方法综述 |
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郑炜1,2,3, 王晓龙1, 陈翔4,5, 夏鑫6, 廖慧玲1, 刘程远1, 孙瑞阳1
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1.西北工业大学 软件学院, 陕西 西安 710072;2.空天地海一体化大数据应用技术国家工程实验室(西北工业大学), 陕西 西安 710072;3.大数据存储与管理工业和信息化部重点实验室(西北工业大学), 陕西 西安 710072;4.南通大学信息科学技术学院, 江苏 南通 226019;5.信息安全国家重点实验室(中国科学院 信息工程研究所), 北京 100093;6.Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia
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| 摘要: |
| 软件缺陷在软件的开发和维护过程中是不可避免的,软件缺陷报告是软件维护过程中重要的缺陷描述文档,高质量的软件缺陷报告可以有效提高软件缺陷修复的效率.然而,由于存在许多开发人员、测试人员和用户与缺陷跟踪系统交互并提交软件缺陷报告,同一个软件缺陷可能被不同的人员报告,导致了大量重复的软件缺陷报告.重复的软件缺陷报告势必加重人工检测重复缺陷报告的工作量,并造成人力物力的浪费,降低了软件缺陷修复的效率.以系统文献调研的方式,对近年来国内外学者在重复软件缺陷报告检测领域的研究工作进行了系统的分析.主要从研究方法、数据集的选取、性能评价等方面具体分析总结,并提出该领域在后续研究中存在的问题、挑战以及建议. |
| 关键词: 缺陷报告 重复检测 深度学习 自然语言处理 信息检索 |
| DOI：10.13328/j.cnki.jos.006367 |
| 分类号:TP311 |
| 基金项目:国家自然科学基金(61972317);教育部重点实验室基金(GDSC202006);信息安全国家重点实验室开放课题(2020-MS-07);陕西省2021年重点研发项目(2021GY-041) |
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| Systematic Literature Review of Duplicated Bug Report Detection Methods |
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ZHENG Wei1,2,3, WANG Xiao-Long1, CHEN Xiang4,5, XIA Xin6, LIAO Hui-Ling1, LIU Cheng-Yuan1, SUN Rui-Yang1
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1.School of Software, Northwestern Polytechnical University, Xi'an 710072, China;2.National Engineering Laboratory for Integrated Aero-space-ground-ocean Big Data Application Technology (Northwestern Polytechnical University), Xi'an 710072, China;3.MIIT Key Laboratory of Big Data Storage and Management (Northwestern Polytechnical University), Xi'an 710072, China;4.School of Information Science and Technology, Nantong University, Nantong 226019, China;5.State Key Laboratory of Information Security (Institute of Information Engineering, Chinese Academy of Sciences), Beijing 100093, China;6.Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia)
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| Abstract: |
| Software bugs are inevitable in the process of software development and maintenance. Software bug reports are an important bug description documents in the software maintenance process. A high-quality software bug report can effectively improve the efficiency of software bug repair. Nevertheless, due to the existence of many developers, testers, and users interact with the bug tracking system and submit bug reports, the same bug may be reported by different parties, resulting in a large number of duplicate software bug reports. Duplicate software bug reports will inevitably increase the workload of manual detection of duplicate bug reports, cause waste of manpower and material resources, and reduce the efficiency of bug repair. This study systematically analyzes the research work of worldwide scholars in the field of duplicated detection of bug reports in recent years by means of literature research. It mainly analyzes and summarizes the research methods, data set selection, performance evaluation, etc, and puts forward the problems and challenges in the follow-up work in this field, and the correspondent's suggestions. |
| Key words: bug report duplicate detection deep learning natural language processing information retrieval |
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