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Automating API Documentation with LLMs: A BERTopic Approach

Published: September 6, 2025 | arXiv ID: 2509.05749v1

By: AmirHossein Naghshzan

Potential Business Impact:

Helps coders find answers faster.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Developers rely on API documentation, but official sources are often lengthy, complex, or incomplete. Many turn to community-driven forums like Stack Overflow for practical insights. We propose automating the summarization of informal sources, focusing on Android APIs. Using BERTopic, we extracted prevalent topics from 3.6 million Stack Overflow posts and applied extractive summarization techniques to generate concise summaries, including code snippets. A user study with 30 Android developers assessed the summaries for coherence, relevance, informativeness, and satisfaction, showing improved productivity. Integrating formal API knowledge with community-generated content enhances documentation, making API resources more accessible and actionable work.

Country of Origin
🇨🇦 Canada

Page Count
3 pages

Category
Computer Science:
Software Engineering