(untitled) (Don Bosco Institute of Technology Delhi Journal of Research, 2025)
Systems with high complexity typically exhibit a balanced combination of order and disorder, characterized by the coexistence of randomness and regularity. In component-based software engineering, each component contributes to overall system complexity through its inherent constraints, interaction mechanisms with other components, and the degree of customizability it supports. As software systems grow in scale and interconnectivity, understanding and managing such complexity becomes critical to ensuring system reliability, maintainability, and quality. Measuring system dependency and interaction complexity provides valuable insights into potential design weaknesses and helps assess software quality at both component and system levels. Complexity metrics play a crucial role in enabling objective comparison across different software systems by applying standardized measurement frameworks. Existing complexity measures, however, often focus primarily on internal code structure, overlooking the significance of component interfaces that govern communication, data exchange, and functional coordination. The author has pointed out a novel interface complexity metric for software components in the study. Based on the quantity, kind, and structural features of interface methods and attributes that a component exposes, the suggested metric measures complexity. Factors such as method signatures, parameter types, data dependencies, access constraints, and interaction frequency are considered to capture the true interaction burden imposed by component interfaces. By focusing on interface-level complexity, the metric provides a more accurate representation of component interdependencies and their impact on overall system behaviour. The proposed approach supports improved software design evaluation, facilitates early detection of architectural vulnerabilities, and aids developers in enhancing modularity, reusability, and long-term system quality.