Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases

Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completing code that requires intensive domain knowledge for example completing the library names. Although there are several wo...

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Veröffentlicht in:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] S. 421 - 433
Hauptverfasser:	Tang, Ze, Ge, Jidong, Liu, Shangqing, Zhu, Tingwei, Xu, Tongtong, Huang, Liguo, Luo, Bin
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 11.09.2023
Schlagworte:	Adaptation models Bayes methods Closed box Codes Data models domain adaptive code completion Predictive models retrieval-augment language model
ISSN:	2643-1572
Online-Zugang:	Volltext
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