Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases-Reference-Cited by-同舟云学术

Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases

Published:2023-09-11 Issue: Volume: Page:
ISSN:
Container-title:2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)
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Author:

Tang Ze¹,Ge Jidong¹,Liu Shangqing²,Zhu Tingwei¹,Xu Tongtong³,Huang Liguo⁴,Luo Bin¹

Affiliation:

1. Nanjing University,National Key Laboratory for Novel Software Technology,China

2. Nanyang Technological University,Singapore

3. Huawei Software Engineering Application Technology,China

4. Southern Methodist University,Department of Computer Science,USA

Funder

National Key Research and Development Program of China

Natural Science Foundation of Jiangsu Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10298258/10298286/10298575.pdf?arnumber=10298575

Reference57 articles.

1. ReACC: A Retrieval-Augmented Code Completion Framework

2. StandUp4NPR: Standardizing SetUp for Empirically Comparing Neural Program Repair Systems

3. Retrieval augmented language model pre-training;guu;International Conference on Machine Learning,2020

4. RAT: A Refactoring-Aware Traceability Model for Bug Localization

5. Generalization through memorization: Nearest neighbor language models;khandelwal;8th International Conference on Learning Representations ICLR 2020,2020

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