Mining API Usage Scenarios from Stack Overflow
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Abstract (arXiv)
We propose a framework to mine API usage scenarios from Stack Overflow. Each task consists of a code example, the task description, and the reactions of developers towards the code example. First, we present an algorithm to automatically link a code example in a forum post to an API mentioned in the textual contents of the forum post. Second, we generate a natural language description of the task by summarizing the discussions around the code example. Third, we automatically associate developers reactions (i.e., positive and negative opinions) towards the code example to offer information about code quality. We evaluate the algorithms using three benchmarks.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Feb 2021.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 0; 2024: 0; 2025: 1.
3 papers.
- 2021Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflowcited by 9
- 2021Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal informationcited by 5
- 2025ArchISMiner: A Framework for Automatic Mining of Architectural Issue-Solution Pairs from Online Developer Communitiescited by 0
- 2025ArchISMiner: A Framework for Automatic Mining of Architectural Issue-Solution Pairs from Online Developer Communities24 Oct 2025
- 2021Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflow27 Nov 2021
- 2021Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information27 Sep 2021