improve-codebase-architecture

To audit a codebase for confusing module boundaries and tight coupling, you map module boundaries to detect single-responsibility violations. This identifies shallow modules, tight coupling, and poor pure function extraction across the frontend and backend.

A codebase architecture becomes hard for AI-assisted development when it contains shallow abstractions, tightly coupled modules, and confusing boundaries. These architectural smells prevent AI tools from effectively interpreting and modifying the code.

To refactor a React frontend and .NET backend for better testability, you assess module boundaries and extract pure functions. A formal refactor plan prioritizes findings with P1-P4 scoring to generate actionable, incremental implementation steps.

Yes, you can use this architecture audit on a full-stack app with React and .NET services. It specifically applies boundary mapping and testability assessment to frontend code in apps/web/src and backend .NET services under services/<Service>/.

The best way to prioritize code refactoring tasks for maintainability is using a P1-P4 priority scoring system. This scores identified architectural smells and generates a concrete refactor plan for high-priority issues to guide incremental implementation.