Home > Published Issues > 2022 > Volume 13, No. 3, June 2022 >
JAIT 2022 Vol.13(3): 213-223
doi: 10.12720/jait.13.3.213-223

Automating Smart Contract Generation on Blockchains Using Multi-modal Modeling

Christian Gang Liu 1, Peter Bodorik 1, and Dawn Jutla 2
1. Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
2. Sobey School of Business, Saint Mary’s University, Halifax, Nova Scotia, Canada

Abstract—The power and correctness of smart contracts have been the focus of much research. We propose a new approach for developing smart contracts that uses multi-modal modeling to represent the application logic for the trade domain. We use discrete events modeling for concurrency combined with FSM modeling to use concurrent FSMs to not only simplify the design process for the modeler, but also to scale the application running on a blockchain and facilitate identifying parts of a smart program that are suitable for off-chain processing on a sidechain that also provides privacy. In addition, we achieve separation of concerns between (a) application logic and (b) its transformation into a smart contract and deployment on a blockchain with processing of selected patterns on private sidechains. We transform the model into a smart contract automatically, such that patterns, selected by the modeler, are deployed on a sidechain. The interface for the mainchain to sidechain interaction is also prepared and deployed automatically.
 
Index Terms—blockchain, smart contract, off-chain computation, FSM modeling, hierarchical state machine, discrete events modeling, multi-modal modeling

Cite: Christian Gang Liu, Peter Bodorik, and Dawn Jutla, "Automating Smart Contract Generation on Blockchains Using Multi-modal Modeling," Journal of Advances in Information Technology, Vol. 13, No. 3, pp. 213-223, June 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.