R.E.F.A.C.T. is a structured methodology for AI-assisted code refactoring. The acronym stands for Review, Extract, Format, Analyze, Clean, and Test — six steps that ensure refactoring improves code quality without introducing regressions.
The R.E.F.A.C.T. methodology provides guardrails for AI-assisted refactoring, ensuring that improvements don't come at the cost of stability.
Understand what you're refactoring before changing anything.
Activities:
AI prompt: "Explain what this code does. What are its inputs, outputs, and side effects?"
Break down large pieces into smaller, focused units.
Activities:
AI prompt: "Identify functions that could be extracted from this code. What would each do?"
Apply consistent formatting and style.
Activities:
AI prompt: "Reformat this code following [your style guide]. Don't change behavior."
Look for deeper issues now that code is cleaner.
Activities:
AI prompt: "Analyze this refactored code. What issues remain? What could still be improved?"
Remove unnecessary code and simplify.
Activities:
AI prompt: "Identify any dead code, unused variables, or unnecessary complexity. What can be safely removed?"
Verify the refactoring didn't break anything.
Activities:
AI prompt: "Generate tests that verify this code still behaves correctly after refactoring."
Each step prepares for the next: