Automatic Generation of Smart Contracts from Real World Contracts in Natural Language

Automatic Generation of Smart Contracts from Real World Contracts in Natural Language

Authors: Krutik Pandya, [Co-author names]
Published in: IEEE 2023 Smart World Congress, Digital Twin Conference
Award: Best Paper Award

Research paper presentation at IEEE 2023 Smart World Congress

Abstract

This paper presents a novel approach for automatically generating blockchain smart contracts from real-world legal contracts written in natural language. Our methodology leverages advanced natural language processing and machine learning techniques to bridge the gap between traditional legal documents and executable blockchain code, addressing significant challenges in contract automation and enforcement.

Introduction

Smart contracts have emerged as a transformative technology for automating contractual agreements on blockchain platforms. However, translating conventional legal contracts into smart contract code remains a labor-intensive, error-prone process requiring specialized expertise in both legal and programming domains.

Methodology

Our approach consists of three main components:

  1. Natural Language Processing Pipeline - For extracting contractual clauses, conditions, and obligations
  2. Semantic Analysis Framework - For interpreting legal requirements and translating them to logical operations
  3. Code Generation Module - For producing secure, efficient smart contract code in Solidity

Results

Our system demonstrated a 78% accuracy rate in correctly translating contractual clauses to smart contract functions across a diverse test set of legal agreements including:

  • Employment contracts
  • Service level agreements
  • Property leases
  • Supply chain contracts

Conclusion

This research represents a significant step toward bridging traditional legal frameworks with blockchain technology, enabling wider adoption of smart contracts across industries while reducing implementation barriers.

Future Work

We aim to extend this work by:

  • Expanding language support beyond English
  • Incorporating regulatory compliance verification
  • Developing domain-specific contract templates for various industries

References

[List of relevant papers and resources]

Code Repository

The implementation code and datasets are available at [GitHub Repository URL]

Acknowledgments

This research was supported by [funding sources/institutions]. We thank our colleagues who provided insight and expertise that greatly assisted the research.