From Requirements to Executable Tests: LLM-Based System Test Generation for REST APIs

Abstract

Modern software systems increasingly rely on APIs, making efficient testing essential for ensuring reliability and correctness. However, creating system tests from natural language requirements is typically a manual and time-consuming process. This research proposes an approach for automatically generating executable REST API tests from natural language requirements using large language models (LLMs) and OpenAPI specifications. A prototype system was developed and evaluated on two real-world APIs. The results show that the approach can generate executable pytest tests, achieve full endpoint reachability coverage, and provide stable automated test execution.