codebase-analysis

To analyze an unfamiliar codebase, you scan dependency manifests, top-level directories, and route entry points to map the tech stack, architecture, and data flow into a structured report. This identifies frameworks, libraries, and folder purposes quickly.

Tracing data flow from user actions through APIs to the UI involves scanning client data-fetching and state patterns. This analysis maps how data moves across the application, including authentication, authorization, and caching behavior.

Detecting implementation gaps and TODO markers across a repository requires enumerating FIXME comments, stubs, placeholder routes, missing tests, and likely security or configurability issues to produce a structured gaps report.

Yes, codebase analysis applies to onboarding, security reviews, and audits of typical web apps. It maps the tech stack, architecture, features, and data flow while surfacing security gaps and incomplete work.

Mapping dependencies and identifying CSS approaches or data-layer tooling requires scanning config and manifest files. This extracts runtime and development libraries, language versions, frameworks, and data-layer tools used in the repository.

A limitation when mapping features and gaps is that the analysis applies to typical web app scenarios, focusing on route entry points and client hooks. It surfaces likely issues but requires manual verification of stubs and security gaps.