Combining text mining and data mining for bug report classification-Reference-Cited by-同舟云学术

Combining text mining and data mining for bug report classification

Published:2016-02-23 Issue:3 Volume:28 Page:150-176
ISSN:2047-7473
Container-title:Journal of Software: Evolution and Process
language:en
Short-container-title:J. Softw. Evol. and Proc.

Author:

Zhou Yu¹²,Tong Yanxiang¹,Gu Ruihang¹,Gall Harald³

Affiliation:

1. College of Computer Science and Technology; Nanjing University of Aeronautics and Astronautics; Nanjing 210016 China

2. State Key Lab. of Novel Software Technology; Nanjing University; Nanjing 210023 China

3. Department of Informatics; University of Zurich; Zurich CH-8050 Switzerland

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Collaborative Innovation Center of Novel Software Technology and Industrialization

Publisher

Wiley

Subject

Software

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/smr.1770/fullpdf

Reference63 articles.

1. Bhattacharya P Neamtiu I Proceedings of the 8th Working Conference on Mining Software Repositories 2011 207 210

2. Giger E Pinzger M Gall H Proceedings of the 2nd International Workshop on Recommendation Systems for Software Engineering 2010 52 56

3. Kim S Zimmermann T Whitehead Jr EJ Zeller A Proceedings of the 29th international conference on Software Engineering 2007 489 498

4. Knab P Pinzger M Bernstein A Proceedings of the 2006 International Workshop on Mining Software Repositories 2006 119 125

5. Lamkanfi A Demeyer S Giger E Mining Software Repositories (MSR), 2010 7th IEEE Working Conference on 2010 1 10

Cited by 98 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. What makes a real change in software performance? An empirical study on analyzing the factors that affect the triagement of performance change points;Science of Computer Programming;2024-03

2. Issue Report Validation in an Industrial Context;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

3. An Empirical Analysis of Rebalancing Methods for Security Issue Report Identification;2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC);2023-10-24

4. An Empirical Study on Bugs Inside PyTorch: A Replication Study;2023 IEEE International Conference on Software Maintenance and Evolution (ICSME);2023-10-01

5. Tag that issue: applying API-domain labels in issue tracking systems;Empirical Software Engineering;2023-08-31