Automatic Comment Generation via Multi-Pass Deliberation-Reference-Cited by-同舟云学术

Automatic Comment Generation via Multi-Pass Deliberation

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
language:
Short-container-title:

Author:

Mu Fangwen¹^ORCID,Chen Xiao¹^ORCID,Shi Lin¹,Wang Song²,Wang Qing¹

Affiliation:

1. Laboratory for Internet Software Technologies, Institute of Software Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China

2. York University, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551349.3556917

Reference59 articles.

1. 2016. Lucene. https://lucene.apache.org/. 2016. Lucene. https://lucene.apache.org/.

2. 2016. Pytorch Framework. https://pytorch.org/. 2016. Pytorch Framework. https://pytorch.org/.

3. 2022. Javalang. https://pypi.org/project/javalang. 2022. Javalang. https://pypi.org/project/javalang.

4. 2022. Project Website. https://github.com/ase-decom/ASE22_DECOM. 2022. Project Website. https://github.com/ase-decom/ASE22_DECOM.

5. 2022. Tokenize. https://docs.python.org/2/library/tokenize.html. 2022. Tokenize. https://docs.python.org/2/library/tokenize.html.

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cross-Modal Retrieval-enhanced code Summarization based on joint learning for retrieval and generation;Information and Software Technology;2024-11

2. RAPID: Zero-Shot Domain Adaptation for Code Search with Pre-Trained Models;ACM Transactions on Software Engineering and Methodology;2024-06-03

3. Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models;Proceedings of the IEEE/ACM 46th International Conference on Software Engineering;2024-04-12

4. Automatic smart contract comment generation via large language models and in-context learning;Information and Software Technology;2024-04

5. Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning;Proceedings of the IEEE/ACM 46th International Conference on Software Engineering;2024-02-06