Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Deep learning-based logging recommendation using merged code representation

Authors
Lee, S.Lee, Y.Lee, C.-G.Woo, H.
Issue Date
Dec-2021
Publisher
Springer Science and Business Media Deutschland GmbH
Keywords
Code embedding; Deep learning; Logging recommendation
Citation
Lecture Notes in Electrical Engineering, v.712, pp 49 - 53
Pages
5
Journal Title
Lecture Notes in Electrical Engineering
Volume
712
Start Page
49
End Page
53
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/44110
DOI
10.1007/978-981-15-9354-3_5
ISSN
1876-1100
Abstract
When developing a large scale software product, it is essential to share a common set of structural coding guidelines and standards among the project team members. In this paper, we propose MergeLogging, a deep learning-based merged network using various code representations for automated logging decisions or other tasks. MergeLogging archives the enhanced recommendation ability that utilizes orthogonal code features from code representations. Our case study with three open-source project datasets demonstrates that logging accuracy can reach as high as 93%.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Software > School of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Chan Gun photo

Lee, Chan Gun
소프트웨어대학 (소프트웨어학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE