cc-data-organization

Auditing code for data organization issues involves running a checklist against variables, data types, and globals to produce a structured status table. This identifies magic numbers, naming violations, and improper global usage while preserving existing behavior.

Fixing magic numbers and improper globals requires a transformer workflow that corrects violations in place while preserving behavior. It replaces hard-coded values with named constants and removes unsafe global state to ensure concurrency safety.

Selecting appropriate modern data types involves applying domain-aligned guidance to choose nullable or optional types and handle temporal data correctly. This ensures safe concurrency and security-sensitive data practices across different languages and architectures.

A code quality audit for data organization applies across languages and architectures typical in software projects. It enforces a checker-applier-transformer workflow to review refactoring workflows, ensuring safe concurrency and proper data type usage regardless of language.

Code review workflows need to check for security-sensitive data and concurrency issues because improper data organization creates unsafe shared state and vulnerabilities. Auditing globals and nullable types ensures temporal data handling remains safe and domain-aligned.