Learning to Represent Programs with Heterogeneous Graphs

Code representation, which transforms programs into vectors with semantics, is essential for source code processing. We have witnessed the effectiveness of incorporating structural information (i.e., graph) into code representations in recent years. Specifically, the abstract syntax tree (AST) and t...

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Bibliographic Details

Published in:	2022 IEEE/ACM 30th International Conference on Program Comprehension (ICPC) pp. 378 - 389
Main Authors:	Zhang, Kechi, Wang, Wenhan, Zhang, Huangzhao, Li, Ge, Jin, Zhi
Format:	Conference Proceeding
Language:	English
Published:	ACM 01.05.2022
Subjects:	code representation Codes Grammar graph neural networks heterogeneous graphs Predictive models Semantics Syntactics Transformers Transforms
ISSN:	2643-7171
Online Access:	Get full text
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