A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning-Reference-Cited by-同舟云学术

A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning

Published:2020-07-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th International Conference on Program Comprehension
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Author:

Liu Fang¹,Li Ge¹,Wei Bolin¹,Xia Xin²,Fu Zhiyi¹,Jin Zhi¹

Affiliation:

1. Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education and Institute of Software, EECS, Peking University, Beijing, China

2. Monash University, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3387904.3389261

Reference40 articles.

1. Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. (2015). Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. (2015).

2. Learning from examples to improve code completion systems

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