Smart Contracts for SMEs and Large Companies
May 28, 2025 Β· Declared Dead Β· π In 2024 IEEE Virtual Conference on Communications (IEEE VCC), 2024
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
C. G. Liu, P. Bodorik, D. Jutla
arXiv ID
2505.22619
Category
cs.SE: Software Engineering
Cross-listed
cs.CR,
cs.DC
Citations
0
Venue
In 2024 IEEE Virtual Conference on Communications (IEEE VCC), 2024
Last Checked
5 months ago
Abstract
Research on blockchains addresses multiple issues, with one being writing smart contracts. In our previous research we described methodology and a tool to generate, in automated fashion, smart contracts from BPMN models. The generated smart contracts provide support for multi-step transactions that facilitate repair/upgrade of smart contracts. In this paper we show how the approach is used to support collaborations via smart contracts for companies ranging from SMEs with little IT capabilities to companies with IT using blockchain smart contracts. Furthermore, we also show how the approach is used for certain applications to generate smart contracts by a BPMN modeler who does not need any knowledge of blockchain technology or smart contract development - thus we are hoping to facilitate democratization of smart contracts and blockchain technology.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted