Аннотация:
Architectural design is pivotal in software development, shaping system functionality and behaviour. This
study consolidates experiences with architectural design metrics to enhance software development
processes and products. Metrics, while not definitive of quality, highlight potential issues and areas for
improvement. Essential properties of effective metrics include simplicity, empirical credibility, consistency,
uniform dimensionality, language independence, and actionable feedback. A systematic mapping study
analysed publications on software architectural design metrics, focusing on quality models and
metamodels. The study identified vital metrics such as coupling, cohesion, complexity, and modularity and
explored their applications in various contexts, including microservices and security. Results indicate a
lack of substantial experience in applying these metrics. The metrics taxonomy includes structural
integrity, adaptability, complexity, maintainability, and traceability, providing a comprehensive framework
for evaluating software architecture. The study emphasises the need for further research to develop
predictive models using architectural metrics, which could improve software quality by proactively
addressing architectural issues. Future efforts should delve into data accumulation and investigate models
for using these metrics for predictive purposes, ultimately enhancing software quality and development
processes.
