Revolutionizing API Documentation through Summarization
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 12 references that are in the map. First posted on arXiv 21 Jan 2024.
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References · 4
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 779
- 2017Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a surveycited by 90
- 2021Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflowcited by 9
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