Automatic generation of natural language summaries for Java classes

Laura Moreno, Jairo Aponte, G. Sridhara, Andrian Marcus, L. Pollock, K. Vijay-Shanker
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引用次数: 311

Abstract

Most software engineering tasks require developers to understand parts of the source code. When faced with unfamiliar code, developers often rely on (internal or external) documentation to gain an overall understanding of the code and determine whether it is relevant for the current task. Unfortunately, the documentation is often absent or outdated. This paper presents a technique to automatically generate human readable summaries for Java classes, assuming no documentation exists. The summaries allow developers to understand the main goal and structure of the class. The focus of the summaries is on the content and responsibilities of the classes, rather than their relationships with other classes. The summarization tool determines the class and method stereotypes and uses them, in conjunction with heuristics, to select the information to be included in the summaries. Then it generates the summaries using existing lexicalization tools. A group of programmers judged a set of generated summaries for Java classes and determined that they are readable and understandable, they do not include extraneous information, and, in most cases, they are not missing essential information.
为Java类自动生成自然语言摘要
大多数软件工程任务要求开发人员理解部分源代码。当面对不熟悉的代码时,开发人员通常依靠(内部或外部)文档来获得对代码的总体理解,并确定它是否与当前任务相关。不幸的是,这些文档经常缺失或过时。本文介绍了一种自动为Java类生成人类可读摘要的技术,假设没有文档存在。摘要允许开发人员理解类的主要目标和结构。摘要的重点是类的内容和职责,而不是它们与其他类的关系。摘要工具决定类和方法原型,并使用它们,结合启发式,选择要包含在摘要中的信息。然后,它使用现有的词汇化工具生成摘要。一组程序员判断了一组为Java类生成的摘要,并确定它们是可读的和可理解的,它们不包括无关的信息,并且在大多数情况下,它们没有遗漏重要的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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