codebase-understanding

To understand an unfamiliar codebase, you can build a queryable knowledge graph that maps repository architecture and component dependencies. This approach automates the extraction of structural relationships to help you onboard quickly.

A codebase knowledge graph is a lightweight, queryable representation of a repository's structure and dependencies. It works by parsing files and symbols to map how code changes impact different components, allowing you to query specific architectural relationships directly.

You can assess the impact of code changes by querying the repository knowledge graph to map diff impacts. This process traces how modifications to specific files or symbols affect downstream components and overall architecture dependencies.

Yes, building a repository dependency graph requires Python and typically depends on libraries like ast, git, and graphviz. The exact dependencies depend on the repository's language and structure to properly parse and visualize the knowledge graph.

The best way to generate a learning plan for a new repository is to build a knowledge graph to map its architecture. This visualizes the codebase structure, allowing you to systematically target key components and understand their dependencies.

Yes, you can visualize codebase architecture automatically by building a lightweight knowledge graph. This process maps files and component dependencies directly from the repository, providing a dashboard to explore the structure without manual mapping.