Applying Engineering Rigor to AI Hallucinations via Property-Based Testing

As AI-generated content becomes increasingly sophisticated yet prone to subtle errors, this experiment demonstrates how property-based testing can serve as a 'truth filter' for verifying logical claims. By treating prose as a specification and applying formal testing harnesses, developers can identify hidden structural requirements and validate the reliability of AI-synthesized research.