Software Architecture and Model-driven Engineering for Blockchain Applications

www.csiro.au
Software Architecture and
Model-driven Engineering for
Blockchain Applications
Ingo Weber | Principal Research Scientist & Team Leader
Architecture & Analytics Platforms (AAP) team
ingo.weber@data61.csiro.au | linkedin.com/in/ingomweber/ | Twitter: @ingomweber
Conj. Assoc. Professor, UNSW Australia | Adj. Assoc. Professor, Swinburne University

Blockchain Background and Terminology
From our recent book:
Xiwei Xu, Ingo Weber, Mark Staples
Architecture for Blockchain Applications
Springer, 2019

Blockchain
5 |
Organization 1 Organization 2 Organization 1 Organization 2
Centralized Trusted Authority
Traditional trusted environment Blockchain trustless environment
Blockchain network

Blockchain 2nd gen – Smart Contracts
Blockchain Smart Contracts:Use and Applicationin BPM | Ingo Weber8 |
• 1st gen Bitcoin transactions are financial transfers
• Now Blockchain ledger can do that, and
store/transact any kind of data
• Blockchain can deploy and execute programs: Smart Contracts
• User-defined code, deployed on and executed by whole
network
• Can enact decisions on complex business conditions
• Can hold and transfer assets, managed by the contract itself
• Ethereum: pay per assembler-level instruction

Visualization of a Blockchain http://ethviewer.live

Blockchain Terminology
From our recent book:
Xiwei Xu, Ingo Weber, Mark Staples.
Architecture for Blockchain Applications.
Springer, 2019.
eBook:
http://dx.doi.org/10.1007/978-3-030-03035-3
Amazon:
http://tinyurl.com/blockchain-architecture-book
Ingo Weber10 |

Blockchain defined (1/4)
• Definition 1 (Distributed Ledger). A Distributed Ledger is an
append-only store of transactions which is distributed across many
machines.
• Definition 2 (Blockchain (Concept)). A Blockchain is a distributed
ledger that is structured into a linked list of blocks. Each block
contains an ordered set of transactions. Typical solutions use
cryptographic hashes to secure the link from a block to its
predecessor.

• Definition 3 (Blockchain System). A Blockchain System
consists of:
• a blockchain network of machines, also called nodes;
• a blockchain data structure, for the ledger that is replicated
across the blockchain network. Nodes that hold a full replica of
this ledger are referred to as full nodes;
• a network protocol that defines rights, responsibilities, and
means of communication, verification, validation, and consensus
across the nodes in the network. This includes ensuring
authorization and authentication of new transactions,
mechanisms for appending new blocks, incentive mechanisms (if
needed), and similar aspects.

• Definition 4 (Public Blockchain). A Public Blockchain is a
blockchain system that has the following characteristics:
• it has an open network where nodes can join and leave as they
please without requiring permission from anyone;
• all full nodes in the network can verify each new piece of data
added to the data structure, including blocks, transactions, and
effects of transactions; and
• its protocol includes an incentive mechanism that aims to ensure
the correct operation of the blockchain system including that
valid transactions are processed and included in the ledger, and
that invalid transactions are rejected.

• Definition 5 (Blockchain Platform). A blockchain platform is the
technology needed to operate a blockchain. This comprises the
blockchain client software for processing nodes, the local data
store for nodes, and any alternative clients to access the
blockchain network.
• Definition 6 (Smart Contract). Smart contracts are programs
deployed as data in the blockchain ledger, and executed in
transactions on the blockchain. Smart contracts can hold and
transfer digital assets managed by the blockchain, and can invoke
other smart contracts stored on the blockchain. Smart contract
code is deterministic and immutable once deployed.
• Definition 7 (dapp). A decentralized application or dapp is a
software system that is designed to provide its main functionality
through smart contracts.

Blockchain Research of the AAP team, Data61

Blockchain Research at Data61
Overview
D61+Live | BlockchainSystems16 |
• Supply Chain / Food
Provenance
• Trade facilitation
• Resource handling
(energy, water, land,
titles)
• Welfare payments
• International trade
• Empirical research on the use of
blockchain
• Dealing with irreversibleblockchain
transactions in software engineering
• Devising approaches, including
model-drivendevelopment tools,
better blockchainclient software,
etc.
• Software Engineering & Architecture
• Business Process Management
• Cyber Security
• Dependability
Approaches
Outcomes
CoreExpertiseDomains
• Distributed Ledger
Technologies
• Blockchain platforms
• Smart contracts
• On/off Blockchain storage
Technology • Identifying design trade-offs
• Identifying Technical Risks &
Opportunities
• Formal and empirical evaluation of
Blockchain systems

Designing Systems with Blockchain
• Design Process, including Suitability Analysis
• A taxonomy of blockchain-based systems for architecture design, X. Xu, I.
Weber, M. Staples et al., ICSA2017.
• The blockchain as a software connector, X. Xu, C. Pautasso, L. Zhu et al.,
WICSA2016.
• Quality Analysis
• Quantifying the cost of distrust: Comparing blockchain and cloud services for
business process execution. P. Rimba, A. B. Tran, I. Weber et al., Information
Systems Frontiers, accepted August 2018 (previously SCAC 2017)
• Comparing blockchain and cloud services for business process execution, P.
Rimba, A. B. Tran, I. Weber et al., ICSA2017.
• Predicting latency of blockchain-based systems using architectural modelling
and simulation, R. Yasaweerasinghelage, M. Staples and I. Weber, ICSA2017.
• Designs & Design Patterns
• A pattern collection for blockchain-based applications. X. Xu, C. Pautasso, L., Q.
Lu, and I. Weber, EuroPLoP 2018
• A platform architecture for multi-tenant blockchain-based systems. I. Weber,
Q. Lu, A. B. Tran, A. Deshmukh, M. Gorski, M. Strazds, ICSA 2019
• Integration with other systems
• EthDrive: A Peer-to-Peer Data Storage with Provenance, X. L. Yu, X. Xu, B. Liu,
CAISE2017.
• Governance and risk management
• Risks and Opportunities for Systems Using Blockchain and Smart Contracts,
Treasury report
Data61 : Preliminary Findings on Blockchain/DLTProjects18 |

Model-driven Engineering
• Business Process Execution
• Untrusted business process monitoring and execution
using blockchain,
I. Weber, X. Xu, R. Riveret et al., BPM 2016
• Optimized Execution of Business Processes on Blockchain,
L. García-Bañuelos, A. Ponomarev, M. Dumas, Ingo Weber,
BPM 2017
• Caterpillar: A blockchain-based business process
management system, O. López-Pintado, L. García-Bañuelos,
M. Dumas, and I. Weber, BPM 2017 Demo
• Runtime verification for business processes utilizing the
Bitcoin blockchain, C. Prybila, S. Schulte, C. Hochreiner, and
I. Weber, FGCS 2018
• Dynamic role binding in blockchain-based collaborative
business processes, O. López-Pintado, M. Dumas, l. García-
Bañuelos, I. Weber
CAISE 2019
• Data / Asset Modeling
• Regerator: a Registry Generator for Blockchain, A. B. Tran,
X. Xu, I. Weber, CAISE 2017 Demo
• Combined Asset & Process Modeling
• Lorikeet: A Model-Driven Engineering Tool for Blockchain-
Based Business Process Execution and Asset Management
A. B. Tran, Q. Lu, I. Weber, BPM 2018 Demo

High and Low-level Views
• High-level Discussions
• How do machine learning, robotic process automation and blockchains affect the human factor in business process
management? Jan Mendling, Gero Decker, Richard Hull, Hajo A. Reijers, and Ingo Weber. Communications of the Association
for Information Systems (CAIS). Peer-reviewed panel paper. Accepted March 2018.
• Blockchains for business process management – challenges and opportunities. Jan Mendling, Ingo Weber, Wil Van Der Aalst,
Jan Vom Brocke, Cristina Cabanillas, Florian Daniel, Søren Debois, Claudio Di Ciccio, Marlon Dumas, Schahram Dustdar, Avigdor
Gal, Luciano García-Bañuelos, Guido Governatori, Richard Hull, Marcello La Rosa, Henrik Leopold, Frank Leymann, Jan Recker,
Manfred Reichert, Hajo A. Reijers, Stefanie Rinderle-Ma, Andreas Solti, Michael Rosemann, Stefan Schulte, Munindar P. Singh,
Tijs Slaats, Mark Staples, Barbara Weber, Matthias Weidlich, Mathias Weske, Xiwei Xu, and Liming Zhu ACM Transactions on
Management Information Systems (TMIS), 9(1):4:1-4:16. Peer-reviewed research commentary. February 2018.
• Empirical Analyses
• On availability for blockchain-based
systems, I. Weber, V. Gramoli et al.,
SRDS 2017
• New kids on the block: an analysis of
modern blockchains, L. Anderson, R.
Holz, A. Ponomarev et al.,
arXiv:1606:06530, 2016

Some Significant Projects
Blockchain | Data61,CSIRO21 |
Australian Treasury-funded (through National Innovation Science Agenda)
• Two reports, launched 6 June 2017
• DLT Foresight
– What might plausibly happen, across
society & economy?
• Technical Risks & Opportunities
– How do needs in various use cases fit
blockchain’s capabilities?
• See www.data61.csiro.au/blockchain
Making Money Smart project with Commonwealth Bank of Australia (CBA)
• Using “programmable money” for conditional payment system contexts
• The money has conditions attached, which are checked before transfers
• Use case: National Disability Insurance Scheme (NDIS)
• See https://www.data61.csiro.au/en/Our-Work/SmartMoney

Red Belly Blockchain (with USyd)
• New technology particularly for private / consortium blockchain
• In lab experiment achieved 660,000 tps with 300 nodes in one
data center, and > 30,000 tps with globally distributed nodes

Architecting Applications on
Blockchain

Overview
• Many interesting applications for Blockchain
• Basically of interest in most lack-of-trust settings where a distributed
application can coordinate multiple parties
• Examples:
– Supply chains
– Handling of titles, e.g., land, water, vehicles
– Identity
• Many startups and initiatives from enterprises / governments
• ... but also many challenges
• When to use blockchain
• Trade-offs in architecture
– Downsides: cost, latency, confidentiality
– What to handle on-chain, what off-chain?

Our work – AAP team
• Architecting applications on Blockchain:
• Book
• Taxonomy and design process
• “Cost of Distrust”: how much more expensive is blockchain?
– On some blockchains, cost and throuhgput are tightly linked
• Availability analysis from viewpoint of dapps
• Latency: simulation under changes
• Model-driven development of smart contracts
• Business process execution
• Model-based generation of code for data structures, non-
fungible and fungible tokens, and UI components

Functions Blockchain can provide in a dapp
• Blockchain as…
Architectural
Element
Communi-
cation
Mechanism
Asset
Management
and Control
Mechanism
Storage
Element
Computational
Element

Blockchains are Not Stand-Alone Systems
UI for humans
IoT
integration
Auxiliary
databases
Legacy
systems
Key
management
private
data
BIG DATA
Blockchain is a component

Non-Functional Trade-Offs
• Compared to conventional database & script engines,
blockchains have:
(-) Confidentiality, Privacy
(+) Integrity, Non-repudiation
(+ read/ - write) Availability
(-) Modifiability
(-) Throughput / Scalability / Big Data
(+ read/ - write) Latency
Security: combination of
CIA properties

Design process

Evaluation of Suitability
Software Architecture and Engineering for Blockchain-based Applications| Ingo Weber31 |

Taxonomy
Blockchain-related design decisions regarding (de)centralisation, with an indication of their relative impact on
quality properties
Legend: ⊕: Less favourable, ⊕⊕: Neutral, ⊕⊕⊕: More favourable

Taxonomy
Blockchain-related design decisions regarding storage and computation, with an
indication of their relative impact on quality properties

Taxonomy
Blockchain-related design decisions regarding blockchain configuration

Cost of Distrust
• RQ: How much more expensive is blockchain over Cloud services?
• Lens: business process execution
• AWS SWF vs. Ethereum public blockchain
– In both cases: pay per instruction
• Experiments on two use cases:
– Incident management (literature)
– 32 instances on public Ethereum vs. 1000 runs on SWF
– Invoicing (industry, 5316 log traces, 65K events)
– Full log replayed on SWF and private Ethereum
• Result:
• Cost models for blockchain and cloud
– Can be adapted easily to current exchange rates
– Allow what-if cost analyses
• 2 orders of magnitude more expensive to use blockchain
– exchange rate: 1 Ether = US$ 11.32 (26/8/2016)
• ~US$ 0.35 per process instance on public blockchain
– outweighed by cost of escrow (if needed) for about US$ 10 of value

Availability
• Availability: the system‘s readiness for correct service
• Blockchain as component: read: +++ ; write: ?
• Ethereum: 12 blocks confirmation is accepted, said to take 3 mins
• Measurements:

Availability
• Potential issue: block gas limit
• Gas limit is set by miners through “voting”
• The sum of Gas of all transactions in a block must be less than the limit
• Response to DDoS attack: lower block gas limit
• Who would be affected by that?

Model-driven Engineering for
Blockchain Applications

Model-driven Engineering & Blockchain
• Model-driven engineering (MDE):
• A methodology for using models at various levels of abstraction and for different
purposes during software development
• Low-level models: production code can be directly derived from the models
• High-level models: means of communication between business owners and
developers implementing a system
• Intermediate levels can support model-based system analysis or system
management tools
• Any level: generate a code skeleton or early version of the code
• Can cover static structures (like data models) or dynamic behavior (activity
sequences)
• Advantages in the blockchain context:
• Code generation can implement best practices and well-tested building blocks
– Code can adhere to blockchain “standards” (like ERC-20, ERC-721, …)
• Models can be independent of specific blockchain technologies or platforms
• Models are often easier to understand than code – particularly useful in
communicating with business partners about smart contracts
– Facilitates building trust
Ingo Weber42 |

MDE for data structures and tokens:
Fungible and Non-fungible Tokens
• Fungible tokens:
interchangeable
• E.g., $2 coin, $10 note
• Main concern: how many?
• Ethereum: ERC20 standard
– Example: OmiseGO (OMG).
“The OmiseGO blockchain comprises a
decentralized exchange, liquidity
provider mechanism, clearinghouse
messaging network, and asset-backed
blockchain gateway. … It uses the
mechanism of a protocol token to create
a proof-of-stake blockchain to enable
enforcement of market activity amongst
participants. Owning OMG tokens buys
the right to validate this blockchain,
within its consensus rules.”
• Non-fungible tokens
• E.g., houses, cars, patents
• Main concern: which ones?
• Ethereum: ERC721
– Example: cryptokitties
https://www.cryptokitties.co
– Kitties are non-fungible,
individual, and their
appearance depends on the
individual features

MDE for data structures and tokens
• Approach:
• Model data structure (variables, types) – not for fungible tokens
• Model relationships to other types / tokens
• Select features
 Code is generated – deploy or customize
• Feature examples:
• Fungible tokens:
– Can be minted? Burnt? By whom?
• Non-fungible tokens
– Include standard method(s) for sale
– One contract for all tokens or one per token?
• Code generated is compliant with standards
 interface syntax and semantics
Ingo Weber44 |

MDE for Processes – Motivation
• Integration of business processes across organizations:
a key driver of productivity gains
• Collaborative process execution
• Doable when there is trust – supply chains can be tightly
integrated
• Problematic when involved organizations have a lack of trust in
each other
 if 3+ parties should collaborate, where to execute the process
that ties them together?
• Common situation in “coopetition”

Motivation: example
Issues:
- Knowing the status, tracking correct execution
- Handling payments
- Resolving conflicts
 Trusted 3rd party ?
 Blockchain!

Approach in a nutshell
• Goal: implement collaborative business processes as smart
contracts
• Translate (enriched) BPMN to smart contract code
• Triggers act as bridge between Enterprise world and blockchain
• Smart contract provides:
– Independent, global process monitoring
– Conformance checking and process enforcement: only expected messages are
accepted, only from the respective role
– Automatic payments & escrow
– Data transformation
– Encryption
• Processes can make use of data / token contracts
• Process activity to hand over title to a car / shipment / grain / ..., e.g.,
in exchange for fungible tokens

Tooling: Design and Runtime

A Pattern Collection
Software Architecture and Engineering for Blockchain-based Applications| Ingo Weber50 |

Summary
• Architecting and developing
applications on Blockchain is challenging
• Our work:
• Software Architecture for Blockchain-based
applications
• Empirical and formal research on
Blockchains
• Model-driven development of smart
contracts
Book available here:
• eBook:
http://dx.doi.org/10.1007/978-3-030-03035-3
• Amazon:
http://tinyurl.com/blockchain-architecture-
book

www.csiro.au
Thank you
Ingo Weber | Principal Research Scientist & Team Leader
ingo.weber@data61.csiro.au | linkedin.com/in/ingomweber/ | Twitter: @ingomweber
Conj. Assoc. Professor, UNSW Australia | Adj. Assoc. Professor, Swinburne University
AAP team Blockchain research: https://research.csiro.au/data61/blockchain/
Blockchain reports: https://www.data61.csiro.au/blockchain/

References (1/3)
1. Xiwei Xu, Ingo Weber, and Mark Staples. Architecture for Blockchain Applications. Springer, 2019
2. Orlenys López-Pintado, Marlon Dumas, Luciano García-Bañuelos, and Ingo Weber. Dynamic role binding in blockchain-based collaborative
business processes. CAISE’19: International Conference on Advanced Information Systems Engineering, Rome, Italy, July 2019
3. Sin Kuang Lo, Xiwei Xu, Chen Wang, Ingo Weber, Paul Rimba, Qinghua Lu, and Mark Staples . Digital-Physical Parity for Food Fraud Detection.
ICBC’19: International Conference on Blockchain, San Diego, USA, June, 2019
4. Ingo Weber, Qinghua Lu, An Binh Tran, Amit Deshmukh, Marek Gorski, and Markus Strazds. A platform architecture for multi-tenant
blockchain-based systems. ICSA’19: IEEE International Conference on Software Architecture, Hamburg, Germany, April 2019
5. Xiwei Xu, Qinghua Lu, Yue Liu, Liming Zhu, Haonan Yao, Athanasios V Vasilakos. Designing blockchain-based applications: A case study for
imported product traceability. Future Generation Computer Systems. Published March 2019
6. Qinghua Lu, Xiwei Xu, Yue Liu, Weishan Zhang, Design Pattern as a Service for Blockchain Applications, ICDMW’2018: IEEE International
Conference on Data Mining Workshops, November 2018
7. An Binh Tran, Qinghua Lu, and Ingo Weber. Lorikeet: A model-driven engineering tool for blockchain-based business process execution and
asset management. In BPM'18: Intl. Conference on Business Process Management, Demo track, Sydney, NSW, Australia, September 2018.
8. Quantifying the cost of distrust: Comparing blockchain and cloud services for business process execution. Paul Rimba, An Binh Tran, Ingo
Weber, Mark Staples, Alexander Ponomarev, and Xiwei Xu. Information Systems Frontiers, Springer, in print, accepted August 2018
9. A Pattern Language for Blockchain-based Applications Xiwei Xu, Cesare Pautasso, Liming Zhu, Qinghua Lu, Ingo Weber EuroPLOP’18:
European Conference on Pattern Languages of Programs, Kloster Irsee, Germany, July 2018
10. Philipp Hoenisch and Ingo Weber. AODV-based Routing for Payment Channel Networks. ICBC’18: International Conference on Blockchain.
June 30, 2018, Seattle, USA
11. Jan Mendling, Gero Decker, Richard Hull, Hajo A. Reijers, and Ingo Weber. How do machine learning, robotic process automation and
blockchains affect the human factor in business process management? Communications of the Association for Information Systems (CAIS).
Peer-reviewed panel paper. Accepted March 2018.

References (2/3)
12. Jan Mendling, Ingo Weber, Wil Van Der Aalst, Jan Vom Brocke, Cristina Cabanillas, Florian Daniel, Søren Debois, Claudio Di Ciccio, Marlon
Dumas, Schahram Dustdar, Avigdor Gal, Luciano García-Bañuelos, Guido Governatori, Richard Hull, Marcello La Rosa, Henrik Leopold, Frank
Leymann, Jan Recker, Manfred Reichert, Hajo A. Reijers, Stefanie Rinderle-Ma, Andreas Solti, Michael Rosemann, Stefan Schulte, Munindar
P. Singh, Tijs Slaats, Mark Staples, Barbara Weber, Matthias Weidlich, Mathias Weske, Xiwei Xu, and Liming Zhu. Blockchains for business
process management – challenges and opportunities. ACM Transactions on Management Information Systems (TMIS), 9(1):4:1-4:16. Peer-
reviewed research commentary. February 2018.
13. Ingo Weber, Vincent Gramoli, Mark Staples, Alex Ponomarev, Ralph Holz, An Binh Tran, and Paul Rimba. On availability for blockchain-based
systems. SRDS’17: IEEE International Symposium on Reliable Distributed Systems, Hong Kong, China, September 2017.
14. Luciano García-Bañuelos, Alexander Ponomarev, Marlon Dumas, and Ingo Weber. Optimized execution of business processes on blockchain.
15th International Conference on Business Process Management (BPM’17), Barcelona, Spain, September 2017.
15. Orlenys López-Pintado, Luciano García-Bañuelos, Marlon Dumas, and Ingo Weber. Caterpillar: A blockchain-based business process
management system. In BPM'17: Intl. Conference on Business Process Management, Demo track, Barcelona, Spain, September 2017.
16. Risks and opportunities for systems using blockchain and smart contracts, Mark Staples, Shiping Chen, Sara Falamaki, Alex Ponomarev, Paul
Rimba, An Binh Tran, Ingo Weber, Xiwei Xu, and Zhenjiang Zhu. Technical report, Data61, CSIRO, Sydney, Australia, June 2017.
17. Regerator: a Registry Generator for Blockchain, An Binh Tran, Xiwei Xu, Ingo Weber, Mark Staples and Paul Rimba. 29th International
Conference on Advanced Information Systems Engineering (CAISE’17).
18. EthDrive: A Peer-to-Peer Data Storage with Provenance, Xiao Liang Yu, Xiwei Xu and Bin Liu. 29th International Conference on Advanced
Information Systems Engineering (CAISE’17).
19. The Balance Attack or Why Forkable Blockchains are Ill-Suited for Consortium, Christopher Natoli and Vincent Gramoli. 2017 IEEE/IFIP
International Conference on Dependable Systems and Networks (DSN’17).
20. Blockchain Consensus, Tyler Crain, Vincent Gramoli, Michel Raynal, Mikel Larrea. Proceedings of AlgoTel 2017.
21. A taxonomy of blockchain-based systems for architecture design, Xiwei Xu, Ingo Weber, Mark Staples, Liming Zhu, Jan Bosch, Len Bass,
Cesare Pautasso and Paul Rimba. 2017 IEEE International Conference on Software Architecture (ICSA’17), Gothenburg, Sweden, April 2017.

References (3/3)
22. Comparing blockchain and cloud services for business process execution, Paul Rimba, An Binh Tran, Ingo Weber, Mark Staples, Alexander
Ponomarev and Xiwei Xu. Short paper, 2017 IEEE International Conference on Software Architecture (ICSA’17), Gothenburg, Sweden, April
2017.
23. Predicting latency of blockchain-based systems using architectural modelling and simulation, Rajitha Yasaweerasinghelage,Mark Staples and
Ingo Weber. Short paper, 2017 IEEE International Conference on Software Architecture (ICSA’17), Gothenburg, Sweden, April 2017.
24. The Blockchain Anomaly, Christopher Natoli, Vincent Gramoli. Proceedings of the 15th IEEE International Symposium on Network Computing
and Applications (NCA’16), IEEE Oct 2016
25. Evaluation of Logic-Based Smart Contracts for Blockchain Systems, Idelberg, Florian and Governatori, Guido and Riveret, Regis and Sartor,
Giovanni. 10th International Web Rule Symposium, July, 2016
26. New kids on the block: an analysis of modern blockchains, Luke Anderson, Ralph Holz, Alexander Ponomarev, Paul Rimba, Ingo Weber.
arXiv:1606:06530, 2016
27. On the Danger of Private Blockchains, Vincent Gramoli. Workshop on Distributed Cryptocurrencies and Consensus Ledgers (DCCL’16), 2016
28. Untrusted business process monitoring and execution using blockchain, Ingo Weber, Sherry Xu, Regis Riveret, Guido Governatori, Alexander
Ponomarev and Jan Mendling. BPM 2016, Rio de Janeiro, Brazil , September, 2016
29. The blockchain as a software connector, Sherry Xu, Cesare Pautasso, Liming Zhu, Vincent Gramoli, Alexander Ponomarev, An Binh Tran and
Shiping Chen. WICSA2016, Venice, Italy, April, 2016

Software Architecture and Model-driven Engineering for Blockchain Applications

More Related Content

What's hot (20)

Similar to Software Architecture and Model-driven Engineering for Blockchain Applications (20)

Recently uploaded (20)

Software Architecture and Model-driven Engineering for Blockchain Applications