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Register a new userIntegrated Model-Driven Engineering of Blockchain Applications for Business Processes and Asset Management
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Added by
Qinghua Lu
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Blockchain has attracted broad interests to build decentralised applications. Blockchain has attracted broad interests to build decentralised applications. However, developing such applications without introducing vulnerabilities is hard for developers, not the least because the deployed code is immutable and can be called by anyone with access to the network. Model-driven engineering (MDE) helps to reduce those risks, by combining proven code snippets as per the model specification, which is easier to understand than source code. Therefore, in this paper, we present an approach for integrated MDE across business processes and asset management (e.g. for settlement). Our approach includes methods for fungible/non-fungible asset registration, escrow for conditional payment, and asset swap. The proposed MDE approach is implemented in a smart contract generation tool called Lorikeet, and evaluated in terms of feasibility, functional correctness, and cost effectiveness.
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Blockchain technology promises a sizable potential for executing inter-organizational business processes without requiring a central party serving as a single point of trust (and failure). This paper analyzes its impact on business process management (BPM). We structure the discussion using two BPM frameworks, namely the six BPM core capabilities and the BPM lifecycle. This paper provides research directions for investigating the application of blockchain technology to BPM.
Developing a software-intensive product or service can be a significant undertaking, associated with unique challenges in each project stage, from inception to development, delivery, maintenance, and evolution. Each step results in artefacts that are crucial for the project outcome, such as source-code and supporting deliverables, e.g., documentation. Artefacts which have inherent value for the organisation are assets, and as assets, they are subject to degradation. This degradation occurs over time, as artefacts age, and can be more immediate or slowly over a period of time, similar to the concept of technical debt. One challenge with the concept of assets is that it seems not to be well-understood and generally delimited to a few types of assets (often code-based), overlooking other equally important assets. To bridge this gap, we have performed a study to formulate a structured taxonomy of assets. We use empirical data collected through industrial workshops and a literature review to ground the taxonomy. The taxonomy serves as foundations for concepts like asset degradation and asset management. The taxonomy can help contextualise, homogenise, extend the concept of technical debt, and serves as a conceptual framework for better identification, discussion, and utilisation of assets.
Internet of Things Driven Data Analytics (IoT-DA) has the potential to excel data-driven operationalisation of smart environments. However, limited research exists on how IoT-DA applications are designed, implemented, operationalised, and evolved in the context of software and system engineering life-cycle. This article empirically derives a framework that could be used to systematically investigate the role of software engineering (SE) processes and their underlying practices to engineer IoT-DA applications. First, using existing frameworks and taxonomies, we develop an evaluation framework to evaluate software processes, methods, and other artefacts of SE for IoT-DA. Secondly, we perform a systematic mapping study to qualitatively select 16 processes (from academic research and industrial solutions) of SE for IoT-DA. Thirdly, we apply our developed evaluation framework based on 17 distinct criterion (a.k.a. process activities) for fine-grained investigation of each of the 16 SE processes. Fourthly, we apply our proposed framework on a case study to demonstrate development of an IoT-DA healthcare application. Finally, we highlight key challenges, recommended practices, and the lessons learnt based on frameworks support for process-centric software engineering of IoT-DA. The results of this research can facilitate researchers and practitioners to engineer emerging and next-generation of IoT-DA software applications.
As the killer application of blockchain technology, blockchain-based payments have attracted extensive attention ranging from hobbyists to corporates to regulatory bodies. Blockchain facilitates fast, secure, and cross-border payments without the need for intermediaries such as banks. Because blockchain technology is still emerging, systematically organised knowledge providing a holistic and comprehensive view on designing payment applications that use blockchain is yet to be established. If such knowledge could be established in the form of a set of blockchain-specific patterns, architects could use those patterns in designing a payment application that leverages blockchain. Therefore, in this paper, we first identify a tokens lifecycle and then present 12 patterns that cover critical aspects in enabling the state transitions of a token in blockchain-based payment applications. The lifecycle and the annotated patterns provide a payment-focused systematic view of system interactions and a guide to effective use of the patterns.
Linear Logic and Defeasible Logic have been adopted to formalise different features of knowledge representation: consumption of resources, and non monotonic reasoning in particular to represent exceptions. Recently, a framework to combine sub-structural features, corresponding to the consumption of resources, with defeasibility aspects to handle potentially conflicting information, has been discussed in literature, by some of the authors. Two applications emerged that are very relevant: energy management and business process management. We illustrate a set of guide lines to determine how to apply linear defeasible logic to those contexts.
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