Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code

Changan Niu; Chuanyi Li; Bin Luo; Vincent Ng

Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code

Software Engineering 2022-05-25 v1 Artificial Intelligence

Authors: Changan Niu , Chuanyi Li , Bin Luo , Vincent Ng

Abstract

Recent years have seen the successful application of deep learning to software engineering (SE). In particular, the development and use of pre-trained models of source code has enabled state-of-the-art results to be achieved on a wide variety of SE tasks. This paper provides an overview of this rapidly advancing field of research and reflects on future research directions.

Keywords

software engineering software engineering education machine learning

Cite

@article{arxiv.2205.11739,
  title  = {Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code},
  author = {Changan Niu and Chuanyi Li and Bin Luo and Vincent Ng},
  journal= {arXiv preprint arXiv:2205.11739},
  year   = {2022}
}

Comments

IJCAI 2022: Survey Track

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