{"title":"TABS: Transforming automatically BPMN models into blockchain smart contracts","authors":"Peter Bodorik , Christian Gang Liu , Dawn Jutla","doi":"10.1016/j.bcra.2022.100115","DOIUrl":null,"url":null,"abstract":"<div><p>Research on blockchains addresses multiple issues, with one being the automated creation of smart contracts. Developing smart contract methods is more difficult than mainstream software development as the underlying blockchain infrastructure poses additional complexity. We report on a new approach to developing smart contracts with the objective of automating the process to increase developer efficiency and reduce the risk of errors introduced by software developers. To support industry adoption, we use Business Process Model and Notation (BPMN) modeling to describe an application while targeting applications in the trade vertical. We describe a system that transforms a BPMN model into a multi-modal model that combines Discrete Event (DE) modeling for concurrency with Hierarchical State Machines (HSMs) to represent application functionality. Then, further transformations are used to transform the DE-HSM model into methods in smart contracts. The system lets the modeler decide which of the independent patterns should be transformed into methods of a separate smart contract that is deployed on a sidechain for the purpose of (i) reducing processing costs and/or (ii) providing privacy so that other participants in the smart contract do not have visibility into the processing of the pattern. We also briefly describe a proof-of-concept tool we built to demonstrate the feasibility of our approach.</p></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"4 1","pages":"Article 100115"},"PeriodicalIF":6.9000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blockchain-Research and Applications","FirstCategoryId":"1093","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096720922000562","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1
Abstract
Research on blockchains addresses multiple issues, with one being the automated creation of smart contracts. Developing smart contract methods is more difficult than mainstream software development as the underlying blockchain infrastructure poses additional complexity. We report on a new approach to developing smart contracts with the objective of automating the process to increase developer efficiency and reduce the risk of errors introduced by software developers. To support industry adoption, we use Business Process Model and Notation (BPMN) modeling to describe an application while targeting applications in the trade vertical. We describe a system that transforms a BPMN model into a multi-modal model that combines Discrete Event (DE) modeling for concurrency with Hierarchical State Machines (HSMs) to represent application functionality. Then, further transformations are used to transform the DE-HSM model into methods in smart contracts. The system lets the modeler decide which of the independent patterns should be transformed into methods of a separate smart contract that is deployed on a sidechain for the purpose of (i) reducing processing costs and/or (ii) providing privacy so that other participants in the smart contract do not have visibility into the processing of the pattern. We also briefly describe a proof-of-concept tool we built to demonstrate the feasibility of our approach.
期刊介绍:
Blockchain: Research and Applications is an international, peer reviewed journal for researchers, engineers, and practitioners to present the latest advances and innovations in blockchain research. The journal publishes theoretical and applied papers in established and emerging areas of blockchain research to shape the future of blockchain technology.