Prompt engineering in LLMs for automated unit test generation: A large-scale study
Wendkûuni C. Ouédraogo·Tegawendé F. Bissyandé·Yinghua Li·Haoye Tian·Anil Koyuncu·Jacques Klein·David Lo·Abdoul Kader Kaboré
Unit testing is essential for software reliability, yet manual test creation is time-consuming and often neglected. Although search-based software testing improves efficiency, it produces tests with poor readability and maintainability. Although LLMs show promise for test generation, existing research lacks comprehensive evaluation across execution-driven assessment, reasoning-based prompting, and real-world testing scenarios. This study presents the first large-scale empirical evaluation of LLM
