Lorikeet: A Model-Driven Engineering Tool for Blockchain-Based Business Process Execution and Asset Management An Binh Tran 0 Qinghua Lu 0 1 Ingo Weber 0 1 Data61, CSIRO , Sydney , Australia School of Computer Science and Engineering , UNSW, Sydney , Australia

Blockchain has attracted broad interest as a distributed ledger technology for building the next generation of applications to address lack-of-trust issues in business. Business processes that manage assets (e.g. transferring car/grain/land titles) are a promising domain for applying blockchain technology: secure asset management (including tokens and crypto-currency) is a major application area of blockchain. Solutions for non-fungible assets (like cars and houses, but also supply chain goods) are recurrently addressed case by case and traditionally rely on a centralised trusted authority. This can cause trust issues and introduce ine ciencies or counterparty risks. However, developing blockchain applications is far from easy, and mistakes may not be xable. Thus, in this paper, we present a model-driven engineering (MDE) tool named Lorikeet for the implementation of business processes on blockchain, which can manage assets. Lorikeet can automatically create well-tested smart contract code from speci cations that are encoded in the business process and data registry models based on the implemented model transformations. We demonstrate the tool with an industrial use case.

 Blockchain Registry Model-Driven Engineering Business Process -

Blockchain is an innovative distributed ledger technology that enables agreements on decentralised and transactional data sharing across a large network of untrusted participants without relying on a central trusted authority. Many organisations (e.g. startups, enterprises, and governments) [ 1, 6 ] are currently exploring how to leverage blockchain technology to build trust in the next generation of applications. Blockchain application areas are diverse, including physical or digital asset registry, tokens, currency, identity management, and business processes.

Management of assets is considered to be the rst \killer application" of blockchain, starting with fungible assets like crypto-currency (Bitcoin, Ether, etc.) and tokens (second-tier coins that are managed on existing blockchain networks like Ethereum). Non-fungible assets (e.g., car or house titles, and titles to supply chain goods) can also be managed using smart contract technology. In contrast to fungible assets, the latter are recurrently solved case by case and are traditionally managed by relying on a centralised trusted authority. This can cause trust issues and introduce ine ciencies or counterparty risks (e.g., re-assigning ownership of goods before payment).

However, building systems on blockchain is non-trivial due to the steep learning curve of the blockchain technology. According to a survey by Gartner [ 4 ], \23 percent of [relevant surveyed] CIOs said that blockchain requires the most new skills to implement of any technology area, while 18 percent said that blockchain skills are the most di cult to nd." Model-driven engineering (MDE) is software engineering methodology that automatically creates software system code from the models. MDE tools can generate well-tested code implementing best practices and help developers manage software complexity by only focusing on building high-level models without requiring expert development knowledge [ 5 ].

In this paper, we present how to leverage MDE to facilitate the development of blockchain applications in the space of business processes and asset registries, which can easily be applied to a broad range of blockchain applications. We designed and implement an MDE tool, named Lorikeet, which can automatically produce smart contracts from business process models and registry data schema. Lorikeet incorporates the registry editor Regerator [ 7 ] and implements the BPMN translation algorithms from both [ 8 ] and [ 2 ]. It is an entirely separate tool from Caterpillar [ 3 ], and tackles the hard challenges of integrating the asset management and business process interactions on blockchain. Lorikeet is in commercial use by Data61, and has been applied in numerous industry projects.

BPMN and registry modeller user interface

REST API gateway

Docker container DNS name: bpmn2solidity

BPMN translator

Docker container DNS name: regerator

Registry generator BPMN and registry modeller & smart contract generator

Fig. 1. Architecture of Lorikeet.

Socket.io server

Message queue

Docker container DNS name: ethtrigger Blockchain trigger Blockchain trigger

 Tool Description

3 https://github.com/bpmn-io/bpmn-js

The BPMN and registry modeller UI interacts with the back-end microservices via an API gateway. The API gateway forwards API calls from the modeller UI, such as translating BPMN model to Solidity, to the corresponding microservice. Fig. 2 shows the business process modeller UI of our tool. Once the user makes changes to the BPMN model on the left-hand side, it is translated to the corresponding Solidity smart contract code which is displayed on the right-hand side. The registry modeller UI is similar to the business process modeller UI. On the left-hand sides is a form collecting the customised registry information. 3

 Maturity, Demo, and Screencast

Lorikeet is a well-evaluated tool that is used for creating blockchain smart contracts in industry and academia. Besides the usual testing, we have used Lorikeet in collaborations with academics internationally and in student projects. We also have completed a number of external blockchain application projects using Lorikeet and received positive feedback from our clients.

For the demo, we will use Lorikeet to model a grain title transfer process use case [ 6 ] and generate smart contract code based on the models. We encountered this use case in our projects and discussions with industry, and modelled it based on publicly available information. Fig. 3 shows a simpli ed grain title transfer process modelled using Lorikeet. There is only one grain title registry interacting with this selected grain title transfer process.

A screencast demonstrating the usage of the Lorikeet tool can be found at https://drive.google.com/open?id=1rpy-oHbDVkXa6u4Fn73wSX8rINn1sv3U .

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