Language Models for Code Completion: A Practical Evaluation

Transformer-based language models for automatic code completion have shown great promise so far, yet the evaluation of these models rarely uses real data. This study provides both quantitative and qualitative assessments of three public code language models when completing real-world code. We first...

Full description

Bibliographic Details

Published in:	Proceedings / International Conference on Software Engineering pp. 956 - 968
Main Authors:	Izadi, Maliheh, Katzy, Jonathan, van Dam, Tim, Otten, Marc, Popescu, Razvan Mihai, van Deursen, Arie
Format:	Conference Proceeding
Language:	English
Published:	ACM 14.04.2024
Subjects:	Analytical models Automatic Code Completion CodeGPT Codes Data models Evaluation IDE InCoder Language Models Open Source Predictive models Training Training data Transformers UniXcoder
ISSN:	1558-1225
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!