improve-codebase-architecture

To refactor shallow modules for better testability, analyze your codebase architecture to identify modules with complex interfaces and simple implementations. This process proposes transformations to deepen modules, improving overall testability and AI navigability.

A deep module in code architecture features a simple interface hiding complex implementation details. Deepening modules enhances testability by isolating dependencies and reducing surface area, making modules easier to test independently and navigate for AI.

Use your project's domain-specific vocabulary and established principles, such as Architecture Decision Records (ADRs), to inform refactoring decisions. This process translates domain language into clear glossaries and principles for guiding module design modifications.

No, analyzing codebase architecture for deepening opportunities requires codebase access. You also need knowledge of project-specific vocabulary and ADRs to effectively communicate refactoring suggestions and establish guiding principles.

The best way to improve module design for AI navigation is to deepen shallow modules by hiding complexity behind simple interfaces. This refactoring approach simplifies dependencies, making the codebase easier for AI to parse and navigate.

While the refactoring approach can identify deepening opportunities, established principles and ADRs are highly recommended. They provide necessary project context and domain language to accurately inform and guide architecture modifications.