🤖 AI Summary
This study addresses the challenge of quantifying the complexity and cost induced by external requirement changes when detailed knowledge of a system’s internal logic is unavailable. To this end, the authors propose a black-box assessment method based on a directed graph of component coupling. By analyzing component interfaces and integrating multi-view modeling—graphical, algebraic, and tabular—the approach uniquely links interface characteristics to cost factors, enabling computable bounded estimates of change-induced complexity and associated costs. The method was validated through a large-scale integration case in a retail banking platform, demonstrating its effectiveness and providing architects and operations teams with actionable, quantitative insights for system design and maintenance.
📝 Abstract
This paper introduces a formal modeling framework designed to estimate the complexity and cost associated with system changes induced by external requirements. We model a system as a directed graph of couplings, capturing the intricate dependencies and information flows between components and elements within a specific context. The proposed method enables the estimation of bounded change complexity through component interfaces, even when internal logic remains opaque. Additionally, the framework provides a mechanism for bounding the cost of system-wide modifications by associating external drivers and cost factors with individual system elements. We propose a multi-view approach to the model, providing graphical, algebraic, and tabular representations to suit different levels of abstraction and computational needs. By bridging the gap between component-based modeling and project cost estimation, our method provides actionable insights for architecture design, software engineering, and lifecycle operations. The model is validated through a case study involving the integration of a large-scale retail banking platform.