improve-codebase-architecture

Improving codebase architecture for testability involves identifying shallow modules and transforming them into deep ones. This refactoring approach enhances module locality and leverage, making codebases easier to test and maintain over time.

Deepening shallow modules during refactoring means restructuring them to hide complex implementation details behind simpler interfaces. This architectural transformation increases testability and AI navigability by improving domain language alignment and code locality.

Finding refactoring opportunities for AI navigability requires analyzing your codebase architecture against domain language principles. By evaluating module depth and interface design, you can surface structural improvements that make code easier for AI agents to parse and navigate.

Using domain language from documentation to guide refactoring ensures code architecture aligns with business concepts. By reading CONTEXT.md and LANGUAGE.md files, architectural improvements maintain consistency with domain principles while increasing testability and module depth.

The best way to propose architectural improvements is by generating plain English descriptions of suggested refactoring. This approach highlights benefits in locality and leverage, explaining how transforming shallow modules into deep ones enhances maintainability without requiring immediate code changes.

Deep module refactoring may not suit codebases lacking clear domain language documentation or those with minimal complexity. If shallow modules already provide adequate testability and AI navigability, forcing architectural depth could introduce unnecessary abstraction layers.