SCOUT: A Scenario-Guided Unit Test Generation Tool for Compact Open-Source LLMs

Abstract

Large language models (LLMs) have shown promising performance in automated unit test generation, but existing approaches often rely on large proprietary or reasoning-oriented models, limiting their practicality for users with limited computational resources. We present SCOUT, a scenario-guided unit test generation tool designed for compact open-source LLMs. Rather than requiring LLMs to reason over raw source code, SCOUT extracts program information through static analysis and progressively provides concise, task-specific contexts for specialized reasoning tasks, including scenario construction and unit test generation. The tool further validates and refines generated tests using compilation, execution, and coverage feedback. Built on an extensible multi-agent architecture, SCOUT provides a fully automated workflow that enables practical unit test generation with locally deployed open-source LLMs on commodity hardware.