Agentic Property-Based Testing: Finding Bugs Across the Python Ecosystem

We developed an agent that can efficiently identify bugs in large software projects. To do this, our agent infers general properties of code that should be true, and then by applying property-based testing—a technique similar to fuzz testing—we are able to discover bugs in top Python packages like NumPy, SciPy, and Pandas. After extensive manual validation, we are in the process of reporting these bugs to the developers, several of which have already been patched.

For more information, read the full paper, take a look at the GitHub repository, or browse the bugs we found at our site.

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