CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training. (arXiv:2205.02029v1 [cs.PL])

Recent years have witnessed increasing interest in code representation
learning, which aims to represent the semantics of source code into distributed
vectors. Currently, various works have been proposed to represent the complex
semantics of source code from different views, including plain text, Abstract
Syntax Tree (AST), and several kinds of code graphs (e.g., Control/Data Flow
Graph). However, most of them only consider a single view of source code
independently, ignoring the correspondences among different views. In this
paper, we propose …

arxiv code learning pl pre-training training