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%.
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- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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