coupling-analysis

Architectural coupling analysis identifies high-risk dependencies by quantifying strength, distance, and volatility across module and service boundaries. It constructs a directed dependency graph to produce a balance-score diagnosis and prioritized refactoring recommendations.

Measuring dependency volatility and strength involves assessing encapsulation levels, architectural boundaries, and subdomain types. By leveraging historical signals, you can infer volatility to prioritize which service couplings require immediate architectural improvements.

Creating a directed dependency graph for module-level boundaries requires structural mapping of your codebase. This maps inter-module dependencies to visualize the coupling graph, allowing you to assess distance and identify structural issues with severity ratings.

Yes, coupling analysis helps decide between extracting a shared contract or duplicating logic by detecting high-strength, distant, volatile couplings. The resulting executive summary and recommendations guide whether to refactor the boundary or duplicate the code.

Generating an executive summary of architectural health issues requires analyzing your codebase's structural dependency map. The analysis identifies coupling issues with assigned severity levels and produces actionable, prioritized recommendations for architectural improvements.