abd-clean-code

To generate clean code, provide a domain story or behavior description and the generator produces runnable Python or JavaScript modules that follow domain language and constructor-based dependency injection. Output is structured with one module per sub-epic and one class per entity.

Constructor-based dependency injection in production code generation means explicit dependencies are provided at object construction rather than hidden internally. This approach enforces clean-code rules by making bounded contexts modular and dependencies visible within small helper functions under 20 lines.

Yes, you can use acceptance criteria and failing tests to generate production-grade code. The generator accepts story descriptions, behavior details, or failing tests as input and validates the resulting Python or JavaScript output against embedded quality scanners to ensure clean-code compliance.

The clean code generator enforces a modular layout for bounded contexts by structuring output with one module per sub-epic area and one class per domain entity. It aligns with clean-code templates and keeps helper functions under 20 lines to maintain production-grade quality.

The best way to refactor ambiguous requirements into runnable code is to identify domain stories and generate modules using domain language. This process turns vague descriptions into structured Python or JavaScript implementations with explicit dependency injection and embedded quality validation.

You should not use automated code generation for refactoring when your domain stories lack clear acceptance criteria or bounded contexts. The generator relies on identifiable domain entities and explicit dependencies, so highly ambiguous or unstructured requirements may not produce valid clean-code output.