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...
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sg-smu-ink.sis_research-54802023-04-04T03:28:16Z PatchNet: A tool for deep patch classification HOANG, Thong LAWALL, Julia OENTARYO, Richard J. TIAN, Yuan LO, David 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 selectparameters 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. 2019-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4477 info:doi/10.1109/ICSE-Companion.2019.00044 https://ink.library.smu.edu.sg/context/sis_research/article/5480/viewcontent/PatchNet_Tool_2019_isce.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Deep learning Patch classification Stable patch identification Software Engineering |
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Deep learning Patch classification Stable patch identification Software Engineering HOANG, Thong LAWALL, Julia OENTARYO, Richard J. TIAN, Yuan LO, David PatchNet: A tool for deep patch classification |
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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 selectparameters 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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text |
author |
HOANG, Thong LAWALL, Julia OENTARYO, Richard J. TIAN, Yuan LO, David |
author_facet |
HOANG, Thong LAWALL, Julia OENTARYO, Richard J. TIAN, Yuan LO, David |
author_sort |
HOANG, Thong |
title |
PatchNet: A tool for deep patch classification |
title_short |
PatchNet: A tool for deep patch classification |
title_full |
PatchNet: A tool for deep patch classification |
title_fullStr |
PatchNet: A tool for deep patch classification |
title_full_unstemmed |
PatchNet: A tool for deep patch classification |
title_sort |
patchnet: a tool for deep patch classification |
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Institutional Knowledge at Singapore Management University |
publishDate |
2019 |
url |
https://ink.library.smu.edu.sg/sis_research/4477 https://ink.library.smu.edu.sg/context/sis_research/article/5480/viewcontent/PatchNet_Tool_2019_isce.pdf |
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