Toward automated verification of unreviewed AI-generated code
Summary
The article argues for shifting from manual review to automated verification of AI-generated code, using constraints like property-based testing, mutation testing, and no-side-effects checks. It discusses an experiment applying these techniques to a FizzBuzz solution to show how verification can constrain the solution space and improve trust in generated code, while noting maintainability concerns. It also references related ideas such as JustHTML and Software Factory.