Speculate: Generating REST API Specifications using LLMs
Krishanu Singh, Kushagra Karar, Abhilash Jindal, Guowei Yang
摘要
REST APIs are widely used for accessing web services. To support their use and testing, developers often write API specifications in open formats like OpenAPI. However, writing these specifications manually is tedious and error-prone, leading to incomplete or outdated specifications that can hinder both API usage and automated testing. Existing tools attempt to generate API specifications from source code using static or dynamic analysis. Unfortunately, these tools are often tightly coupled to specific languages and frameworks, making them hard to generalize and extend. This paper presents Speculate, the first approach to combine lightweight static analysis with large language models (LLMs) to automatically generate REST API specifications from source code. By leveraging LLMs trained on diverse codebases, Speculate generalizes easily across languages and frameworks. We evaluate Speculate on 19 real-world web repositories spanning two programming languages and three REST frameworks. Our results show that Speculate outperforms existing tools on both precision and recall across all dimensions.
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