Analyzability

Analyzability is a software quality notion describing how easily a system can be examined to understand its structure, behavior, and the causes of defects or performance anomalies. In standards such as ISO/IEC 25010, it is treated as a subcharacteristic of maintainability, though the term is used informally in broader engineering contexts. A highly analyzable system allows developers and operators to locate responsible components, reason about the effects of changes, and diagnose failures with minimal effort.

Several factors influence analyzability. Code readability, modular architecture, clear interfaces, and explicit dependencies improve understanding. Comprehensive documentation, architecture diagrams, and consistent naming also help. Observability features—logging, tracing, metrics—provide evidence about runtime behavior. Legacy code, dense coupling, and heterogeneous technologies tend to reduce analyzability. Metrics such as cyclomatic complexity, coupling, cohesion, and depth of inheritance, along with qualitative assessments from reviews, are commonly used to gauge it.

Improving analyzability typically involves design practices that promote clarity and isolation, such as modular design, well-defined APIs, and domain-driven approaches. Tooling for static analysis, automated testing, and structured change management further enhance it. Analyzability is closely related to maintainability and to the broader idea of transparency, and it should be considered during system evolution to support faster debugging, safer refactoring, and more reliable incident response.