Title
GANCoder: An Automatic Natural Language-to-Programming Language Translation Approach based on GAN
Abstract
We propose GANCoder, an automatic programming approach based on Generative Adversarial Networks (GAN), which can generate the same functional and logical programming language codes conditioned on the given natural language utterances. The adversarial training between generator and discriminator helps generator learn distribution of dataset and improve code generation quality. Our experimental results show that GANCoder can achieve comparable accuracy with the state-of-the-art methods and is more stable when programming languages.
Year
DOI
Venue
2019
10.1007/978-3-030-32236-6_48
NLPCC (2)
DocType
ISSN
Citations 
Conference
NLPCC 2019: Natural Language Processing and Chinese Computing
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Zhu Yabing100.34
Yanfeng Zhang217015.56
Yang Huili300.34
Wang Fangjing400.34