Explores dynamic symbolic execution to improve semantic difference analysis in component-and-connector architectures, indicating potential benefits and challenges in scalability.
In model-driven development, ensuring the correctness and consistency of evolving models is critical. This paper explores the use of Dynamic Symbolic Execution (DSE) for semantic difference analysis of Component and Connector (C&C) architectures, exemplified on MontiArc models. We extended the existing MontiArc-to-Java generator to capture both symbolic and concrete execution data at runtime, including transition conditions, visited states, and automata variables. This data enables the identification of key execution traces that reveal system behavior. We evaluate execution strategies based on runtime efficiency, minimality, and completeness. Finally, we asses DSE’s applicability in semantic difference analysis. Our results show that DSE offers promise for analyzing component-and-connector architectures, though scalability remains a challenge.
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Grahl et al. (2026) studied this question.
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