@inproceedings{e759c9c4631a4372a61d1c4e0fb3fc25,
title = "Deep learning-based logging recommendation using merged code representation",
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\%.",
keywords = "Code embedding, Deep learning, Logging recommendation",
author = "Suin Lee and Youngseok Lee and Lee, \{Chan Gun\} and Honguk Woo",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.; International Conference on IT Convergence and Security, ICITCS 2020 ; Conference date: 19-08-2020 Through 21-08-2020",
year = "2021",
doi = "10.1007/978-981-15-9354-3\_5",
language = "English",
isbn = "9789811593536",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "49--53",
editor = "Hyuncheol Kim and Kim, \{Kuinam J.\}",
booktitle = "IT Convergence and Security - Proceedings of ICITCS 2020",
}