review-architecture

Architecture review automation scans your source code to identify incorrect layering, single-source-of-truth violations, and semantic inconsistencies. It parses the codebase to detect architectural patterns, generating detailed reports with specific source code references and line numbers.

Single-source-of-truth violation detection analyzes source code to locate semantic inconsistencies and policy drift where data or logic is duplicated incorrectly. It parses the codebase to trace architectural patterns and flags violations, reporting specific file references and line numbers.

Checking code changes for architectural best practices involves scanning the codebase to detect layering violations and single-source-of-truth issues. This reduces technical debt risk by ensuring new code adheres to established architectural standards through automated pattern analysis.

Automated code analysis reports semantic inconsistencies by parsing and analyzing source code for architectural patterns. It generates detailed reports highlighting issues with specific references to source code and line numbers, identifying problems like incorrect layering and policy drift.

Automating architectural pattern detection requires parsing and analyzing source code, meaning its effectiveness depends on codebase structure and language support. It identifies layering, single-source-of-truth, and semantic issues but may require integration into existing development workflows to reduce technical debt effectively.