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Learning Sequential and Structural Information for Source Code Summarization

Published • Jan 1, 2021
NobleIDNI2P00W75R31S40
Authors:
YunSeok Choi
,
JinYeong Bak
,
CheolWon Na

Abstract

We propose a model that learns both the sequential and the structural features of code for source code summarization. We adopt the abstract syntax tree (AST) and graph convolution to model the structural information and the Transformer to model the sequential information. We convert code snippets in...

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