🤖 AI Summary
This work addresses the compliance monitoring latency arising from the semantic gap between natural-language contracts and smart contracts. Methodologically, it introduces an integrated framework that combines legal-semantic modeling with automated code generation: legal contract templates are user-assistedly refined using the Symboleo formal language, and a specification translation algorithm automatically generates monitor-enabled smart contracts deployable on Hyperledger Fabric. The key contribution is an end-to-end, formally verifiable automation pipeline that maps legal obligations directly to executable, runtime-enforceable contract logic. Experimental evaluation demonstrates that the framework significantly reduces the development cycle for compliance-aware smart contracts and validates its effectiveness and deployability in proactive contractual compliance monitoring scenarios.
📝 Abstract
Monitoring the compliance of contract performance against legal obligations is important in order to detect violations, ideally, as soon as they occur. Such monitoring can nowadays be achieved through the use of smart contracts, which provide protection against tampering as well as some level of automation in handling violations. However, there exists a large gap between natural language contracts and smart contract implementations. This paper introduces a Web-based environment that partly fills that gap by supporting the user-assisted refinement of Symboleo specifications corresponding to legal contract templates, followed by the automated generation of monitoring smart contracts deployable on the Hyperledger Fabric platform. This environment, illustrated using a sample contract from the transactive energy domain, shows much potential in accelerating the development of smart contracts in a legal compliance context.