FACOS: Finding API Relevant Contents on Stack Overflow with Semantic and Syntactic Analysis
Abstract
Finding relevant API content on Stack Overflow is a critical yet time-consuming task for developers. FACOS (Finding API Contents On Stack Overflow) combines semantic and syntactic analysis to automatically surface Stack Overflow posts most relevant to a given API query, outperforming keyword-based baselines by leveraging both code structure and natural language semantics.
Overview
Stack Overflow is the primary resource for developers seeking API usage examples, error explanations, and best practices. However, finding the most relevant posts for a specific API query remains a challenge — keyword search often surfaces too many irrelevant results, while semantic search alone misses syntactically precise matches.
FACOS (Finding API Contents On Stack Overflow) addresses this by combining:
- Semantic analysis: leveraging PTMs to understand the intent behind API-related queries and map them to conceptually similar Stack Overflow discussions.
- Syntactic analysis: using code structure and API call signatures to identify posts with exact or near-exact API usage patterns.
Approach
FACOS fuses both signals into a unified ranking model, trained and evaluated on a curated benchmark of API queries paired with their ground-truth relevant Stack Overflow posts. The hybrid approach consistently outperforms pure semantic and pure syntactic baselines.
Published at: arXiv preprint arXiv:2111.07238, 2021 · Citations: 7
Mohammad Abdul Hadi
AI Security Researcher (Sr. Software Engineer)
AI Security Researcher at Huawei R&D — LLM architecture, malware analysis, and agentic multi-agent systems. 150+ citations across A* and A-rated conferences.