PatchNet: A tool for deep patch classification

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, differenti...

全面介紹

Saved in:
書目詳細資料
Main Authors: HOANG, Thong, LAWALL, Julia, OENTARYO, Richard J., TIAN, Yuan, LO, David
格式: text
語言:English
出版: Institutional Knowledge at Singapore Management University 2019
主題:
在線閱讀:https://ink.library.smu.edu.sg/sis_research/4527
https://ink.library.smu.edu.sg/context/sis_research/article/5530/viewcontent/PatchNet_Tool_2019_isce_av.pdf
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Singapore Management University
語言: English
實物特徵
總結: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. Our video demonstrating PatchNet and PatchNet implementation are publicly available at https://goo.gl/CZjG6X and https://github.com/hvdthong/PatchNetTool respectively.