利用深度学习技术自动生成评论的文献综述

P. Singh, Saransh Sharma
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引用次数: 0

摘要

在软件开发过程中,编写了数千行代码,如果没有适当的注释,开发人员就很难阅读代码。自动注释生成通过为源代码生成注释来克服这个问题。许多研究人员已经在研究源代码中的自动注释生成,有些人已经发表了他们的研究成果,但是在源代码中的自动注释生成领域还有很多需要改进的地方。在本文中,我们将解释和回顾在注释生成中使用的深度学习技术,以使代码易于阅读。在源代码中自动生成注释变得至关重要,因为任何开发人员都可以在不花费太多时间的情况下轻松理解它。因此,理解CNN、RNN、LSTM等深度学习技术是如何使在源代码中自动生成注释成为可能的,以及为什么研究人员现在转向深度学习技术来自动生成注释,这一点非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Literature Review on Automatic Comment Generation using Deep Learning Techniques
During the development of software, thousands of lines of codes are written and without proper comments it gets difficult for the developers to read the code. Automatic Comment Generation overcomes this problem by generating comments for the source code. Many researchers are already working on automatic comment generation in the source code and some have already published their results but still there is lot of scope of improvement in the field of automatic generation of comments in the source code. In this paper, we will be explaining and reviewing deep learning techniques that areused in comment generation to make the code easily readable. Generating comments automatically become crucial in the source code for any developer to understand it easily without spending much time. Hence, it's very important to understand how deep learning techniques like CNN, RNN, LSTM and others are making it possible to generate automatic comments in source code and also why researchers have now shifted on deep learning techniques to do automatic comment generation.
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