基于大数据的开源项目缺陷报告智能预检技术

席圣渠; 徐锋; 陈鑫; 李宣东

doi:10.11959/j.issn.2096-0271.2021004

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基于大数据的开源项目缺陷报告智能预检技术

专题：数据驱动的软件智能化开发 | 更新时间：2024-06-03

- 基于大数据的开源项目缺陷报告智能预检技术
- Big-data based intelligent bug triage techniques for open-source projects
- 大数据 2021年7卷第1期页码：2021004-1
- 作者机构：
  
  1. 南京大学计算机科学与技术系，江苏南京 210023
  2. 计算机软件新技术国家重点实验室（南京大学），江苏南京 210023
- 作者简介：
  
  [ "席圣渠（1992- ），男，南京大学计算机科学与技术系博士生，主要研究方向为基于深度学习的软件智能开发方法" ]
  [ "徐锋（1975- ），男，博士，南京大学计算机科学与技术系教授、博士生导师，主要研究方向为智能化软件可信术" ]
  [ "陈鑫（1975- ），男，博士，南京大学计算机科学与技术系副教授，主要研究方向为嵌入式系统、软件建模与分、软件测试与验证" ]
  [ "李宣东（1963- ），男，博士，南京大学计算机科学与技术系教授、博士生导师，软件学院院长，主要研究方向为软件建模与分析、软件测试与验证" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2016YFB1000800);国家自然科学基金资助项目;The National Natural Science Foundation of China(61672274);国家自然科学基金资助项目;The National Natural Science Foundation of China(61702252);江苏省协同创新中心项目;Collaborative Innovation Center of Novel Software Technology and Industrialization of Jiangsu Province
- DOI：10.11959/j.issn.2096-0271.2021004
  中图分类号： G434
- 网络首发：2021-01，
  
  纸质出版：2021-01-15
- 稿件说明：
移动端阅览
席圣渠, 徐锋, 陈鑫, 等. 基于大数据的开源项目缺陷报告智能预检技术[J]. 大数据, 2021,7(1):2021004-1.

Shengqu XI, Feng XU, Xin CHEN, et al. Big-data based intelligent bug triage techniques for open-source projects[J]. Big Data Research, 2021, 7(1): 2021004-1.
席圣渠, 徐锋, 陈鑫, 等. 基于大数据的开源项目缺陷报告智能预检技术[J]. 大数据, 2021,7(1):2021004-1. DOI： 10.11959/j.issn.2096-0271.2021004.

Shengqu XI, Feng XU, Xin CHEN, et al. Big-data based intelligent bug triage techniques for open-source projects[J]. Big Data Research, 2021, 7(1): 2021004-1. DOI： 10.11959/j.issn.2096-0271.2021004.

摘要

缺陷报告预检目标在于确定优先级和修复措施，是保障软件可信的关键环节。然而，在日益普及的开源项目中，由于缺陷数量众多、缺乏组织管理等特性，人工预检难以及时完成，迫切需要基于大数据的自动化、智能化预检技术。结合工业界、学术界对缺陷报告预检的认知，提出了一种智能化缺陷报告预检技术框架，全面系统地归纳了缺陷报告预检中存在的3个关键任务：缺陷优先级分类、缺陷分派、缺陷再分派，并结合开源项目的特点提出了相关技术。实验结果初步验证了上述技术的合理性和有效性。

Abstract

Bug triage aims to determine the priority and repair measures and is critical in ensuring software trustability. However

in the increasingly popular open-source projects

due to a large number of defects and lack of organization and management

it is challenging to triage all the bug reports by hand on time

making big-data based

automated and intelligent bug triage urgent. An intelligent bug triage technical framework based on industry and academia’s cognition was proposed

and three key tasks: bug priority classification

bug assignment

and bug reassignment

were identified comprehensively and systematically. Related technologies for the characteristics of open-source projects were proposed. The preliminary experiment results show the reasonableness and effectiveness of the above techniques.

关键词

Keywords

references

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