C
CIOPages
CIO Intelligence Suite — interactive apps with an AI co-pilot.
Assessments

Architecture Entropy Index

Measure the degree of architectural decay across your codebase. Identify where patterns have diverged, boundaries have eroded, and coupling has crept in — before technical debt becomes unmanageable.

Assessment Dimensions

Rate each dimension on a 1–10 scale based on your organization

1 / 10

How many different patterns exist for solving the same problem across your codebase. Includes API design styles, error handling approaches, state management strategies, and data access patterns that vary without clear rationale.

Low (1)High (10)
1 / 10

Frequency of architectural boundary crossings — services calling internal methods of other services, shared database access across domains, or UI components directly querying data stores. Each violation erodes the intended architecture.

Low (1)High (10)
1 / 10

Divergence in coding conventions, formatting, naming, and structural organization across the codebase. Includes inconsistent use of linting rules, mixed paradigms (OOP vs. functional), and varying levels of type safety.

Low (1)High (10)
1 / 10

How often implementation details bleed through abstractions. Includes leaking database schemas into API responses, exposing infrastructure concerns in business logic, and tight coupling to framework internals.

Low (1)High (10)

Assessment Dimensions (cont.)

Continue rating each dimension below

1 / 10

Repeated structural patterns that have diverged over time — copied-and-modified services, forked libraries, or parallel implementations that started identical but drifted apart without consolidation.

Low (1)High (10)
1 / 10

Gradual increase in coupling between components that were designed to be independent. Includes growing shared state, expanding service interfaces, and increasing coordination requirements for deployments.

Low (1)High (10)
1 / 10

Volume of unused code, abandoned feature flags, deprecated endpoints still running, and orphaned configuration. Dead code obscures intent, increases cognitive load, and creates false positives in tooling.

Low (1)High (10)
1 / 10

Inconsistency in naming conventions across services, databases, APIs, and variables. Includes misleading names, abbreviation inconsistency, and domain terms that mean different things in different contexts.

Low (1)High (10)