Verify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis
The paper addresses reliability issues in AI agents that make probabilistic predictions without checking evidence. It proposes execution-grounded closed-loop reasoning, where an agent plans, executes tests in isolated environments, and only repairs code if execution confirms a problem exists. This method ensures trustworthy results across different programming languages.