code2seq: Generating Sequences from Structured Representations of Code

Alon Uri
Alon Uri
Brody Shaked
Brody Shaked

ICLR, 2019.

Cited by: 0|Bibtex|Views35
EI
Other Links: arxiv.org|dblp.uni-trier.de

Abstract:

The ability to generate natural language sequences from source code snippets has a variety of applications such as code summarization, documentation, and retrieval. Sequence-to-sequence (seq2seq) models, adopted from neural machine translation (NMT), have achieved state-of-the-art performance on these tasks by treating source code as a ...More

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