PatchNet: A Tool for Deep Patch Classification
February 16, 2019 ยท Entered Twilight ยท ๐ 2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
"Last commit was 5.0 years ago (โฅ5 year threshold)"
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Repo contents: .gitignore, .idea, README.md, deeplearning, preprocessing
Authors
Thong Hoang, Julia Lawall, Richard J. Oentaryo, Yuan Tian, David Lo
arXiv ID
1903.02063
Category
cs.SE: Software Engineering
Cross-listed
cs.LG
Citations
18
Venue
2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
Repository
https://github.com/hvdthong/PatchNetTool
โญ 26
Last Checked
1 month ago
Abstract
This work proposes PatchNet, an automated tool based on hierarchical deep learning for classifying patches by extracting features from commit messages and code changes. PatchNet contains a deep hierarchical structure that mirrors the hierarchical and sequential structure of a code change, differentiating it from the existing deep learning models on source code. PatchNet provides several options allowing users to select parameters for the training process. The tool has been validated in the context of automatic identification of stable-relevant patches in the Linux kernel and is potentially applicable to automate other software engineering tasks that can be formulated as patch classification problems. A video demonstrating PatchNet is available at https://goo.gl/CZjG6X. The PatchNet implementation is available at https://github.com/hvdthong/PatchNetTool.
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