This research rigorously evaluates large language models' ability to understand code beyond superficial pattern recognition, with important implications for code security and engineering.

• Introduces novel metrics to quantify LLMs' code comprehension capabilities
• Assesses models' effectiveness in identifying bugs and understanding program functionality
• Reveals limitations in current LLMs' deeper semantic understanding of code
• Highlights security implications when deploying LLMs for critical code analysis tasks

For security professionals, this research provides crucial insights into the reliability of AI-powered code analysis tools and identifies potential vulnerabilities in automated security checking processes.

How Accurately Do Large Language Models Understand Code?