=Paper=
{{Paper
|id=Vol-2196/BPM_2018_paper_12
|storemode=property
|title=Lorikeet: A Model-Driven Engineering Tool for Blockchain-Based Business Process Execution and Asset Management
|pdfUrl=https://ceur-ws.org/Vol-2196/BPM_2018_paper_12.pdf
|volume=Vol-2196
|authors=An Binh Tran,Qinghua Lu,Ingo Weber
|dblpUrl=https://dblp.org/rec/conf/bpm/TranLW18
}}
==Lorikeet: A Model-Driven Engineering Tool for Blockchain-Based Business Process Execution and Asset Management==
https://ceur-ws.org/Vol-2196/BPM_2018_paper_12.pdf
Lorikeet: A Model-Driven Engineering Tool for
Blockchain-Based Business Process Execution
and Asset Management
An Binh Tran1 , Qinghua Lu1,2 , and Ingo Weber1,2
1
Data61, CSIRO, Sydney, Australia
2
School of Computer Science and Engineering, UNSW, Sydney, Australia
firstname.lastname@data61.csiro.au
Abstract. 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 ap-
plying blockchain technology: secure asset management (including tokens
and crypto-currency) is a major application area of blockchain. Solu-
tions 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
inefficiencies or counterparty risks. However, developing blockchain ap-
plications is far from easy, and mistakes may not be fixable. Thus, in this
paper, we present a model-driven engineering (MDE) tool named Lori-
keet for the implementation of business processes on blockchain, which
can manage assets. Lorikeet can automatically create well-tested smart
contract code from specifications that are encoded in the business process
and data registry models based on the implemented model transforma-
tions. We demonstrate the tool with an industrial use case.
Keywords: Blockchain · Model-Driven Engineering · Business Process
· Registry
1 Introduction
Blockchain is an innovative distributed ledger technology that enables agree-
ments 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 gen-
eration of applications. Blockchain application areas are diverse, including physi-
cal or digital asset registry, tokens, currency, identity management, and business
processes.
Management of assets is considered to be the first “killer application” of
blockchain, starting with fungible assets like crypto-currency (Bitcoin, Ether,
F. Casati et al. (Eds.): Proceedings of the Dissertation Award and Demonstration, Industrial Track
at BPM 2018, CEUR-WS.org, 2018. Copyright c 2018 for this paper by its authors. Copying
permitted for private and academic purposes. This volume is published and copyrighted by its
editors.
2 Tran et al.
etc.) and tokens (second-tier coins that are managed on existing blockchain net-
works 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 inefficiencies or counterparty risks (e.g.,
re-assigning ownership of goods before payment).
However, building systems on blockchain is non-trivial due to the steep learn-
ing 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 difficult to find.” Model-driven engineering (MDE) is soft-
ware 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 automati-
cally 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 as-
set 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 Socket.io server
Message queue
Docker container Docker container Docker container
DNS name: bpmn2solidity DNS name: regerator DNS name: ethtrigger
BPMN translator Registry generator Blockchain trigger
BPMN and registry modeller & smart contract generator Blockchain trigger
Fig. 1. Architecture of Lorikeet.
Lorikeet 3
2 Tool Description
Fig. 1 illustrates the architecture of Lorikeet, which consists of a modeller user
interface (UI), and three back-end components including BPMN translator, Reg-
istry generator and blockchain trigger. The modeller UI component is presented
as a web application for users to build business process and registry models.
The business process modeller is extended from the bpmn-js modelling library3 .
Business processes are modelled in the Business Process Model and Notation
(BPMN) 2.0, while registries are modelled as in Regerator [7].
We extend BPMN 2.0 to support representation of and interaction with reg-
istries in the BPMN process model. The extension comprises two new elements,
RegistryReference and ActionInvocation, which consist of new graphical nota-
tions and new XML attributes. A RegistryReference represents an asset data
store on a blockchain while an ActionInvocation shows the asset registry ac-
tion to invoke. On the registry side, the registry modeller provides a form for
users to fill in the registry model input. The registry model consists of four
parts, including basic information (registry name, description, user-defined data
fields and their types), registry type (single or distributed), basic operations
(Create/Read/Update/Delete and existence checking for each record) and ad-
vanced operations (record lifecycle management and foreign key). Specifically, we
propose an access control policy to be enforced on registry record lifecycle man-
agement actions, such as create, update, delete and transfer ownership.
We provide an option to allow individual registry record lifecycle actions to be
managed by a process instance. For an action invocation from the process in-
stance to the registry, changes to the registry record are finalised only after the
execution of process step logic is completed: the process instance smart contract
calls the registry contract function. Since registry actions could fail, there is a
checkbox on Lorikeet’s user interface for atomic behaviour across registry ac-
tions and business process tasks: if marked as atomic, the registry update and
the process state change either both fail or succeed.
Back-end components, including BPMN translator, registry generator, as well
as blockchain trigger, are built adhering to a microservice-based architecture and
deployed independently as Docker containers. The BPMN translator can auto-
matically generate smart contracts in Solidity from BPMN models while the
registry generator creates Solidity smart contract based on the registry models.
The BPMN translator takes an existing BPMN business process model as input
and outputs a smart contract. This output includes the information to call reg-
istry functions and to instantiate and execute the process model. The registry
generator takes data structure information and registry type as fields, and basic
and advanced operations as methods, from which it generates the registry smart
contract. Users can then deploy the smart contracts on blockchain. The trig-
ger communicates with an Ethereum blockchain node, and handles compilation,
deployment and interaction with Solidity smart contracts.
3
https://github.com/bpmn-io/bpmn-js
4 Tran et al.
Fig. 2. Graphical interface of Lorikeet.
The BPMN and registry modeller UI interacts with the back-end microser-
vices via an API gateway. The API gateway forwards API calls from the modeller
UI, such as translating BPMN model to Solidity, to the corresponding microser-
vice. 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 con-
tracts 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 Lori-
keet 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 simplified 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 .
Lorikeet 5
Fig. 3. Grain title transfer process model built using Lorikeet.
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