codebase-analysis

Codebase analysis systematically uncovers entry points, dependency chains, and architectural patterns to map how code is organized. Start by identifying primary entry points, trace module relationships, detect patterns like MVC or layered architecture, and surface technical debt hotspots to build a complete understanding of the project.

Entry-point discovery locates where execution begins, then dependency tracing maps import and export flows between modules. This reveals which components depend on each other, helping you understand the code flow and find the critical paths to focus on first.

Yes, codebase analysis applies across languages and frameworks. The workflow adapts to each ecosystem's conventions—identifying entry points, mapping dependencies, and detecting architectural patterns work for any modern codebase regardless of technology stack.

Technical debt identification surfaces hotspots, missing test coverage, and aging code paths during analysis. This reveals maintenance risks and refactoring priorities, helping teams plan cleanup and modernization efforts strategically.

Conduct codebase analysis before refactoring to map dependencies, detect patterns, and locate debt. Understanding the architecture and relationships prevents breaking changes and ensures refactoring targets the highest-impact areas first.

Codebase analysis uncovers the current structure, patterns, and debt through systematic exploration. Architecture review uses those findings to evaluate design decisions and alignment with goals, making analysis the foundational step for any review.