Pith. sign in

REVIEW

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2205.11739 v1 pith:IZYEM7ZR submitted 2022-05-24 cs.SE cs.AI

classification cs.SEcs.AI
keywords codedeepengineeringlearningmodelspre-trainedresearchsoftware
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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.

Discussion (0). Continue with ORCID to comment.

Pith tools