Program Generation and Code Completion Techniques Based on Deep Learning: Literature Review
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National Program on Key Basic Research Project of China (973) (2015CB352201); National Natural Science Foundation of China (61620106007, 61751210)

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    Abstract:

    Automatic software development has always been a research hotspot in the field of software engineering. Currently, Internet technology has promoted the development of open source software and open source communities. These large-scale code and data are opportunities for automatic software development. At the same time, deep learning is beginning to be applied in various software engineering tasks. How to use deep learning technology for large-scale code learning and realize automatic programming of machines is a common expectation in the field of artificial intelligence and software engineering. The machine automatically writes program to assist or even replace the programmer to develop the program to a certain extent, which greatly reduces the development burden of the programmer and improves the efficiency and quality of the software development. At present, automatic programming based on deep learning methods is mainly implemented from two aspects, program generation and code completion. This study introduces these two aspects and the deep learning models.

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胡星,李戈,刘芳,金芝.基于深度学习的程序生成与补全技术研究进展.软件学报,2019,30(5):1206-1223

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  • Received:August 31,2018
  • Revised:October 31,2018
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  • Online: May 08,2019
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