Automatically recommending components for issue reports using deep learning

Choetkiertikul, M, Dam, HK, Tran, Truyen, Pham, T, Ragkhitwetsagul, C and Ghose, A 2021, Automatically recommending components for issue reports using deep learning, Empirical Software Engineering, vol. 26, no. 2, pp. 1-39, doi: 10.1007/s10664-020-09898-5.

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Title Automatically recommending components for issue reports using deep learning
Author(s) Choetkiertikul, M
Dam, HK
Tran, TruyenORCID iD for Tran, Truyen orcid.org/0000-0001-6531-8907
Pham, T
Ragkhitwetsagul, C
Ghose, A
Journal name Empirical Software Engineering
Volume number 26
Issue number 2
Article ID 14
Start page 1
End page 39
Total pages 39
Publisher Springer
Place of publication Berlin, Germany
Publication date 2021
ISSN 1382-3256
1573-7616
Keyword(s) Software engineering analytics
Component recommendation
Recommendation systems for software engineering
Mining software repositories
Deep learning
Science & Technology
Technology
Computer Science, Software Engineering
Computer Science
DUPLICATE BUG REPORTS
NATURAL-LANGUAGE
SEVERITY
Language eng
DOI 10.1007/s10664-020-09898-5
Indigenous content off
Field of Research 0803 Computer Software
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30148174

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