Regression Testing
is the process of retesting an AI or machine learning system after changes to verify that existing functionality and performance have not been negatively affected.
What is Regression Testing?
Regression testing compares a system's behavior before and after updates such as model changes, code modifications, data updates, or configuration changes. It can involve testing known inputs, expected outputs, safety controls, and performance metrics to identify unintended changes.
Why is Regression Testing Important?
Regression testing helps teams detect problems introduced by updates before they affect production users. For AI systems, it can also help verify that improvements in one area have not caused unexpected degradation in accuracy, safety, reliability, or other previously validated behaviors.
Common use cases
Regression testing is commonly used after model updates, prompt changes, software releases, dataset changes, policy updates, and modifications to AI application workflows.