Duplicate Bug Report Detection: How Far Are We?

被引:6
|
作者
Zhang, Ting [1 ]
Han, Donggyun [2 ]
Vinayakarao, Venkatesh [3 ]
Irsan, Ivana Clairine [1 ]
Xu, Bowen [1 ]
Thung, Ferdian [1 ]
Lo, David [1 ]
Jiang, Lingxiao [1 ]
机构
[1] Singapore Management Univ, Singapore, Singapore
[2] Royal Holloway Univ London, London, England
[3] Chennai Math Inst, Chennai, Tamil Nadu, India
基金
新加坡国家研究基金会;
关键词
Bug reports; duplicate bug report detection; deep learning; empirical study; PERFORMANCE;
D O I
10.1145/3576042
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Many Duplicate Bug Report Detection (DBRD) techniques have been proposed in the research literature. The industry uses some other techniques. Unfortunately, there is insufficient comparison among them, and it is unclear how far we have been. This work fills this gap by comparing the aforementioned techniques. To compare them, we first need a benchmark that can estimate how a tool would perform if applied in a realistic setting today. Thus, we first investigated potential biases that affect the fair comparison of the accuracy of DBRD techniques. Our experiments suggest that data age and issue tracking system (ITS) choice cause a significant difference. Based on these findings, we prepared a new benchmark. We then used it to evaluate DBRD techniques to estimate better how far we have been. Surprisingly, a simpler technique outperforms recently proposed sophisticated techniques on most projects in our benchmark. In addition, we compared the DBRD techniques proposed in research with those used in Mozilla and VSCode. Surprisingly, we observe that a simple technique already adopted in practice can achieve comparable results as a recently proposed research tool. Our study gives reflections on the current state of DBRD, and we share our insights to benefit future DBRD research.
引用
收藏
页数:32
相关论文
共 50 条
  • [41] Duplicate Data Detection Using GNN
    Lu, Hanrong
    Chen, Xin
    Lan, Xuhui
    Zheng, Feng
    PROCEEDINGS OF 2016 IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA 2016), 2016, : 167 - 170
  • [42] How far can we go? Determining the optimal loan size in progressive lending
    Dhib, Nahla
    Ashta, Arvind
    STRATEGIC CHANGE-BRIEFINGS IN ENTREPRENEURIAL FINANCE, 2021, 30 (04): : 389 - 404
  • [43] Unlocking the microbial studies through computational approaches: how far have we reached?
    Kumar, Rajnish
    Yadav, Garima
    Kuddus, Mohammed
    Ashraf, Ghulam Md
    Singh, Rachana
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (17) : 48929 - 48947
  • [44] Unlocking the microbial studies through computational approaches: how far have we reached?
    Rajnish Kumar
    Garima Yadav
    Mohammed Kuddus
    Ghulam Md Ashraf
    Rachana Singh
    Environmental Science and Pollution Research, 2023, 30 : 48929 - 48947
  • [45] Generating Python']Python Type Annotations from Type Inference: How Far Are We?
    Guo, Yimeng
    Chen, Zhifei
    Chen, Lin
    Xu, Wenjie
    Li, Yanhui
    Zhou, Yuming
    Xu, Baowen
    ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2024, 33 (05)
  • [46] Learning Profiles in Duplicate Question Detection
    Saedi, Chakaveh
    Rodrigues, Joao
    Silva, Joao
    Branco, Antonio
    Maraev, Vladislav
    2017 IEEE 18TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IEEE IRI 2017), 2017, : 544 - 550
  • [47] It's Not a Bug, It's a Feature: How Misclassification Impacts Bug Prediction
    Herzig, Kim
    Just, Sascha
    Zeller, Andreas
    PROCEEDINGS OF THE 35TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2013), 2013, : 392 - 401
  • [48] Two Decades of Sustainability Management Tools for SMEs: How Far Have We Come?
    Johnson, Matthew P.
    Schaltegger, Stefan
    JOURNAL OF SMALL BUSINESS MANAGEMENT, 2016, 54 (02) : 481 - 505
  • [49] Biologically plausible deep learning - But how far can we go with shallow networks?
    Illing, Bernd
    Gerstner, Wulfram
    Brea, Johanni
    NEURAL NETWORKS, 2019, 118 : 90 - 101
  • [50] Inviscid approach for upwind sails aerodynamics. How far can we go?
    Aubin, N.
    Augier, B.
    Bot, P.
    Hauville, F.
    Floch, R.
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2016, 155 : 208 - 215