This research introduces TESTEVAL, a comprehensive benchmark for evaluating large language models' capabilities in generating effective test cases for software.

• Addresses the lack of fair comparisons between different LLMs for test case generation
• Focuses on Python program testing, helping detect bugs and vulnerabilities
• Establishes a standardized framework for assessing LLM performance in software testing tasks
• Provides insights for engineering teams seeking to integrate AI into their testing workflows

For engineering professionals, this research offers valuable guidance on which LLMs perform best for automated test generation, potentially reducing testing time and improving code quality.

TESTEVAL: Benchmarking Large Language Models for Test Case Generation