Graph-Based Smart Contract Querying and Reuse
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Solution Overview
Problem
Existing smart contracts and contract information models often rely on program instructions or industry-specific data structures, making them difficult to generalize, compare, or reuse across different contexts due to minor differences in contract details.
Innovation Solution
A process and system that construct, interpret, enforce, analyze, and reuse terms for smart contracts using a directed graph representing the contract state, allowing for systematic and unambiguous handling across various fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If smart contracts use program instructions or industry-specific data structures, then they can be implemented with specific functionality, but they become difficult to generalize, compare, or reuse across different contexts
Solution Approach 1:
The patent applies universality by creating a standardized graph-based data structure that can represent multiple types of smart contracts and their relationships in a unified format. This graph structure serves as a universal model that can accommodate different contract types, industries, and contexts while maintaining a consistent representation framework, thereby enabling reuse across different applications without requiring separate complex models for each contract type.
Solution Approach 2:
The patent segments contract information into discrete graph components (nodes and edges) that represent specific contractual elements and their relationships. By breaking down complex contracts into modular graph elements that can be independently defined and combined, the system enables flexible recombination of contract terms and conditions, making it easier to generalize and reuse contract patterns across different contexts while reducing overall model complexity.
2Ease of operation
If smart contracts are represented using natural language documents, then they are easier to understand, but they cannot be efficiently processed or analyzed by automated systems
Solution Approach 1:
The patent introduces a graph-based data structure as an intermediary representation layer between natural language contract documents and automated processing systems. This intermediate graph format preserves the semantic meaning and structure of natural language contracts while organizing information in a machine-readable format that enables efficient automated querying, analysis, and processing, thus bridging the gap between human readability and computational efficiency.
Data Source
AI summary
A process includes receiving a request via an API, determining a query based on a set of query parameters, and determining a target graph portion template based on the query, where the request includes a callback address. The process may include searching a set of directed graphs to determine a set of graph portions based on the query. Each respective directed graph of the set of directed graphs may include a set of vertices and a set of directed edges connecting respective pairs of vertices among the set of vertices, where each respective vertex of the set of vertices is associated with a respective category label of a set of mutually exclusive categories. The process may include selecting a set of event records and sending a value of the set of event records to the callback address.