Modeling the composition of analysis components and automatic constraint checking for semantic soundness

Component-based software architecture enables software architects to design complex systems by composing components that interact through well-defined, syntactically specified interfaces. A special kind of component we investigated in our previous work is the analysis components. Analysis components support the evaluation and prediction of system’s functional and non-functional properties. Evaluating these properties early in the development process helps optimize system performance and ensure compliance with requirements. While approaches for modeling and analyzing such systems, such as the Palladio approach, support syntactic validation of the composition, they often lack mechanisms to ensure the semantic soundness of compositions. In this paper, we present a model transformation approach to help architects ensure that system models are semantically sound and behave as expected. This approach enables the transformation of Palladio models into MontiArc models, allowing architects to enrich their system representations with semantic constraints and validate these constraints with the MontiArc workbench. This ensures that component interactions are consistent with both structural composition and intended semantics. We evaluate our approach through two different case studies. From these case studies, we derived several scenarios with varying constraints and states to assess the accuracy and performance of our approach. To evaluate accuracy, we examined our approach’s ability to check semantic constraints and detect violations. We observed high accuracy across the case studies. For performance, we analyze time complexity in different constraint types. The approach performed well when applied to arithmetic constraints, with its effectiveness decreasing when applied to more complex string-centered constraints.