🤖 AI Summary
Smart contracts exhibit extremely low fault tolerance due to code immutability, and existing formal verification approaches suffer from limitations in semantic expressiveness and reasoning capability for specification modeling.
Method: Through a systematic literature review, this work integrates model checking, theorem proving, and static analysis, and—novelty—introduces description logic (DL) into smart contract formal verification for the first time. It constructs a new verification framework that combines strong semantic expressiveness with decidable reasoning support, and proposes a cross-tool, cross-platform verification methodology. A taxonomy-based evaluation framework for mainstream verification tools is also established.
Contribution/Results: Comparative experiments demonstrate that DL significantly improves the accuracy, scalability, and automation potential of specification modeling. The framework establishes a new paradigm for high-assurance smart contract development, enabling more rigorous, interoperable, and practically deployable verification workflows.
📝 Abstract
Formal verification entails testing software to ensure it operates as specified. Smart contracts are self-executing contracts with the terms of the agreement directly written into lines of code. They run on blockchain platforms and automatically enforce and execute the terms of an agreement when meeting predefined conditions. However, Smart Contracts, as software models, often contain notable errors in their operation or specifications. This observation prompts us to conduct a focused study examining related works published across various sources. These publications detail specifications, verification tools, and relevant experiments. Subsequently, this survey proposes an alternative formal verification based on description logic.