Code Completion using Neural Attention and Byte Pair Encoding
@article{Arkesteijn2020CodeCU, title={Code Completion using Neural Attention and Byte Pair Encoding}, author={Youri Arkesteijn and Nikhil Saldanha and Bastijn Kostense}, journal={ArXiv}, year={2020}, volume={abs/2004.06343} }
In this paper, we aim to do code completion based on implementing a Neural Network from Li et. al.. Our contribution is that we use an encoding that is in-between character and word encoding called Byte Pair Encoding (BPE). We use this on the source code files treating them as natural text without first going through the abstract syntax tree (AST). We have implemented two models: an attention-enhanced LSTM and a pointer network, where the pointer network was originally introduced to solve out… CONTINUE READING
Figures, Tables, and Topics from this paper
References
SHOWING 1-6 OF 6 REFERENCES
Code Completion with Neural Attention and Pointer Networks
- Computer Science
- IJCAI
- 2018
- 54
- Highly Influential
- PDF
A Survey of Machine Learning for Big Code and Naturalness
- Computer Science
- ACM Comput. Surv.
- 2018
- 291
- PDF
Byte Pair Encoding: a Text Compression Scheme That Accelerates Pattern Matching
- 1999
- 66
- Highly Influential
Code completion with neural aention and pointer networks. arXiv preprint arXiv:1711.09573
- 2017
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Computer Science
- ACL 2016
- 2016
- 284