Towards Code Summarization of APIs Based on Unofficial Documentation Using NLP Techniques

TL;DR

This paper presents an NLP-based method to generate API summaries from unofficial documentation, providing a useful supplement to official docs to aid developers in understanding APIs more effectively.

Contribution

It introduces an automatic approach leveraging unofficial documentation and NLP techniques for API summarization, which is a novel contribution in this area.

Findings

Generated summaries are competitive with existing methods.

Summaries can effectively assist developers in understanding APIs.

Approach enhances API documentation with minimal manual effort.

Abstract

Each programming language comes with official documentation to guide developers with APIs, methods, and classes. However, in some cases, official documentation is not an efficient way to get the needed information. As a result, developers may consult other sources (e.g., Stack Overflow, GitHub) to learn more about an API, its implementation, usage, and other information that official documentation may not provide. In this research, we propose an automatic approach to generate summaries for APIs and methods by leveraging unofficial documentation using NLP techniques. Our findings demonstrate that the generated summaries are competitive, and can be used as a complementary source for guiding developers in software development and maintenance tasks.