Revolutionizing API Documentation through Summarization (2401.11361v1)
Abstract: This study tackles the challenges associated with interpreting Application Programming Interface (API) documentation, an integral aspect of software development. Official API documentation, while essential, can be lengthy and challenging to navigate, prompting developers to seek unofficial sources such as Stack Overflow. Leveraging the vast user-generated content on Stack Overflow, including code snippets and discussions, we employ BERTopic and extractive summarization to automatically generate concise and informative API summaries. These summaries encompass key insights like general usage, common developer issues, and potential solutions, sourced from the wealth of knowledge on Stack Overflow. Software developers evaluate these summaries for performance, coherence, and interoperability, providing valuable feedback on the practicality of our approach.
- Grootendorst, M. (2022). BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203.05794.
- Naghshzan, A. (2022). Towards Code Summarization of APIs Based on Unofficial Documentation Using NLP Techniques. arXiv preprint arXiv:2208.06318.
- Miller, D. (2019). Leveraging BERT for extractive text summarization on lectures. arXiv preprint arXiv:1906.04165.
Sponsor
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.