使用ccg从源代码生成注释

Sergey Matskevich, Colin S. Gordon
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引用次数: 7

摘要

好的注释可以帮助开发人员更快地理解软件并提供更好的维护。然而,注释经常缺失,通常不准确,或者过时。自动注释生成可以避免许多这样的问题。本文提出了一种利用自然语言处理中的通用技术直接从源代码生成信息注释的方法。我们使用现有的自然语言模型生成注释,该模型将单词与其各自的逻辑含义和语法规则结合起来,允许通过搜索程序文本的声明性描述来生成注释。我们用Python实现的几个经典算法来评估我们的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generating comments from source code with CCGs
Good comments help developers understand software faster and provide better maintenance. However, comments are often missing, generally inaccurate, or out of date. Many of these problems can be avoided by automatic comment generation. This paper presents a method to generate informative comments directly from the source code using general-purpose techniques from natural language processing. We generate comments using an existing natural language model that couples words with their individual logical meaning and grammar rules, allowing comment generation to proceed by search from declarative descriptions of program text. We evaluate our algorithm on several classic algorithms implemented in Python.
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