Formalizing smart contract design patterns with DCR graphs

Journal article, 2026

Smart contracts manage blockchain assets and embody business processes. Yet, mainstream languages lack explicit support forprocess concepts such as roles, action dependencies, and time constraints, leading to increased implementation complexity andanalysis challenges. To address this, we use Dynamic Condition Response (DCR) graphs, a formal business process modelinglanguage, to formalize the semantics of smart contract business logic. Modeling smart contracts in DCR graphs involvestranslating their underlying behavioral logic into a declarative visual model using DCR's explicit constructs for events, roles,data, time, and inter-event relationships. Furthermore, we systematically model 15 common high-level smart contractdesignpatterns, representing recurring solutions to business logic-level problems. These formalizations reduce ambiguity comparedto informal descriptions and serve as language-independent specifications. We demonstrate the modeling process throughthree complete smart contract case studies that combine six design patterns. Our modeling methodology, formalizations, andcorrespondence between smart contract semantics and DCR graphs enable future automated analysis and verification.