计算机科学技术学报 ›› 2019,Vol. 34 ›› Issue (5): 942-956.doi: 10.1007/s11390-019-1953-5

所属专题： Software Systems

• Special Section on Software Systems 2019 • 上一篇    下一篇

基于缺陷报告传递序列建模的缺陷分派方法

Sheng-Qu Xi1, Yuan Yao1,*, Member, CCF, Xu-Sheng Xiao2, Member, ACM, IEEE, Feng Xu1, Member, CCF, Jian Lv1, Fellow, CCF   

  1. 1 State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China;
    2 Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland Ohio 44106-7071, U.S.A
  • 收稿日期:2019-03-01 修回日期:2019-08-05 出版日期:2019-08-31 发布日期:2019-08-31
  • 通讯作者: Yuan Yao E-mail:y.yao@nju.edu.cn
  • 作者简介:Sheng-Qu Xi currently is a Ph.D. student of a five-year educational system in State Key Laboratory for Novel Software, the Department of Computer Science and Technology at Nanjing University, Nanjing. He received his B.S. degree in computer science from Nanjing University, Nanjing, in 2014. His major research interest includes mining bug reports and deep learning for software engineering.
  • 基金资助:
    This work is supported by the National Natural Science Foundation of China under Grant Nos. 61690204, 61672274, and 61702252, and the Collaborative Innovation Center of Novel Software Technology and Industrialization at Nanjing University.

Bug Triaging Based on Tossing Sequence Modeling

Sheng-Qu Xi1, Yuan Yao1,*, Member, CCF, Xu-Sheng Xiao2, Member, ACM, IEEE, Feng Xu1, Member, CCF, Jian Lv1, Fellow, CCF   

  1. 1 State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China;
    2 Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland Ohio 44106-7071, U.S.A
  • Received:2019-03-01 Revised:2019-08-05 Online:2019-08-31 Published:2019-08-31
  • Contact: Yuan Yao E-mail:y.yao@nju.edu.cn
  • About author:Sheng-Qu Xi currently is a Ph.D. student of a five-year educational system in State Key Laboratory for Novel Software, the Department of Computer Science and Technology at Nanjing University, Nanjing. He received his B.S. degree in computer science from Nanjing University, Nanjing, in 2014. His major research interest includes mining bug reports and deep learning for software engineering.
  • Supported by:
    This work is supported by the National Natural Science Foundation of China under Grant Nos. 61690204, 61672274, and 61702252, and the Collaborative Innovation Center of Novel Software Technology and Industrialization at Nanjing University.

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补充材料

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缺陷分派是软件开发与维护中不可或缺的一环，其目的在于为缺陷报告选择合适的修复者。研究者们尝试采用机器学习、信息检索的方法为给定缺陷报告选择合适的修复者，以优化缺陷分派流程。然而，已有方法尚未同时考虑下述三个关乎缺陷分派准确性的方面：1）缺陷报告的文本信息；2）缺陷报告的元数据；3）缺陷报告传递序列。为同时使用这三种信息，提出了一种序列到序列的模型同时训练文本与传递序列信息，随后将训练好的文本、传递序列特征同元数据特征相结合，共同输入到分类模型以完成预测。在三个不同开源项目的实验中，本文方法在准确性方面比较当前最先进有显著提升。

关键词: 缺陷分派, 缺陷报告传递序列, 软件仓库挖掘

Abstract: Bug triaging, which routes the bug reports to potential fixers, is an integral step in software development and maintenance. To make bug triaging more efficient, many researchers propose to adopt machine learning and information retrieval techniques to identify some suitable fixers for a given bug report. However, none of the existing proposals simultaneously take into account the following three aspects that matter for the efficiency of bug triaging:1) the textual content in the bug reports, 2) the metadata in the bug reports, and 3) the tossing sequence of the bug reports. To simultaneously make use of the above three aspects, we propose iTriage which first adopts a sequence-to-sequence model to jointly learn the features of textual content and tossing sequence, and then uses a classification model to integrate the features from textual content, metadata, and tossing sequence. Evaluation results on three different open-source projects show that the proposed approach has significantly improved the accuracy of bug triaging compared with the state-of-the-art approaches.

Key words: bug triaging, tossing sequence, software repository mining

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