An enhanced approach for automatic annotation of error codes based on Seq2edit
The deep natural language translation models have been used for automatic code error correction and have demonstrated outstanding potential. However, a large and accurately annotated training dataset is essential for these models to perform well. The key to improving the performance of these models...
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Main Authors: | Jian Wang, Tao Lin, Rongsen Zhao, Huiling Zhao |
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Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2025-07-01
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Series: | PeerJ Computer Science |
Subjects: | |
Online Access: | https://peerj.com/articles/cs-3024.pdf |
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