Executable Models and Instance Tracking for Decentralized Applications on Blockchains and Cloud Platforms -- Metamodel and Implementation

Decentralized applications rely on non-centralized technical infrastructures and coordination principles. Without trusted third parties, their execution is not controlled by entities exercising centralized coordination but is instead realized through technologies supporting distribution such as blockchains and serverless computing. Executing decentralized applications with these technologies, however, is challenging due to the limited transparency and insight in the execution, especially when involving centralized cloud platforms. This paper extends an approach for execution and instance tracking on blockchains and cloud platforms permitting distributed parties to observe the instances and states of executable models. The approach is extended with (1.) a metamodel describing the concepts for instance tracking on cloud platforms independent of concrete models or implementation, (2.) a multidimensional data model realizing the concepts accordingly, permitting the verifiable storage, tracking, and analysis of execution states for distributed parties, and (3.) an implementation on the Ethereum blockchain and Amazon Web Services (AWS) using state machine models. Towards supporting decentralized applications with high scalability and distribution requirements, the approach establishes a consistent view on instances for distributed parties to track and analyze the execution along multiple dimensions such as specific clients and execution engines.Comment: This is an unpublished preprint; both versions archived on arXiv.org have not been published. Although initially intended for publication, the preprint has undergone further improvements and has been utilized as input for new publications. (see also: https://www.unifr.ch/inf/digits/en/group/team/haerer.html

A Cross-Chain Query Language for Application-Level Interoperability Between Open and Permissionless Blockchains

Open and permissionless blockchains are distributed systems with thousands to tens of thousands of nodes, establishing novel platforms for decentralized applications. When realizing such an application, data might be stored and retrieved from one or more blockchains by distributed network nodes without relying on centralized coordination and trusted third parties. Data access could be provided through a query language such as SQL at the application level, establishing a unified view on application-level data that is verifiably stored. However, when accessing multiple blockchains through their node software and APIs, interoperability cannot be assumed today, resulting in challenges of inhomogeneous data access. In addition, different feature sets and trade-offs exist, e.g., regarding smart contract functionality, availability, distribution, scalability, and security. For increasing interoperability, the paper at hand suggests pursuing the development of a cross-chain query language at the application level. The language abstracts from implementation by providing a standardized syntax, an integrated data model, and a processing architecture for data queries. This research is an extended and updated paper demonstrating the language syntax, data model, and architecture with an evaluation of compatibility against the largest open and permissionless blockchains today.Comment: Version 2 with changed template. arXiv admin note: text overlap with arXiv:2209.0722

Towards Interoperability of Open and Permissionless Blockchains: A Cross-Chain Query Language

The rise of open and permissionless blockchains has introduced novel platforms for applications based on distributed data storage. At the application and business levels, long-established query languages such as SQL provide interoperability that can be complemented by blockchain-based data storage today, enabling permissionless and verifiable data storage along with decentralized execution across tens of thousands of nodes. However, when accessing one or more blockchains, interoperability is not provided today, posing challenges such as inhomogeneous data access in addition to different features and trade-offs, e.g. in data and distribution, scalability, and security. Towards interoperability in data access among the increasing number of blockchain platforms, this paper introduces a cross-chain query language for data access across blockchains. Similar to SQL, the language abstracts from implementation based on a data model compatible with the largest open and permissionless blockchains (OPB) today. The language, data model, and processing architecture are demonstrated and evaluated with an implemented prototype, aiming to contribute to the discussion on blockchain interoperability among OPB.Comment: Copyright 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Conceptual Model Interpreter for Large Language Models

Large Language Models (LLMs) recently demonstrated capabilities for generating source code in common programming languages. Additionally, commercial products such as ChatGPT 4 started to provide code interpreters, allowing for the automatic execution of generated code fragments, instant feedback, and the possibility to develop and refine in a conversational fashion. With an exploratory research approach, this paper applies code generation and interpretation to conceptual models. The concept and prototype of a conceptual model interpreter is explored, capable of rendering visual models generated in textual syntax by state-of-the-art LLMs such as Llama~2 and ChatGPT 4. In particular, these LLMs can generate textual syntax for the PlantUML and Graphviz modeling software that is automatically rendered within a conversational user interface. The first result is an architecture describing the components necessary to interact with interpreters and LLMs through APIs or locally, providing support for many commercial and open source LLMs and interpreters. Secondly, experimental results for models generated with ChatGPT 4 and Llama 2 are discussed in two cases covering UML and, on an instance level, graphs created from custom data. The results indicate the possibility of modeling iteratively in a conversational fashion.Comment: ER Forum 2023, 42nd International Conference on Conceptual Modeling (ER 2023), November 6-9, 2023, Lisbon, P

Vom SOM-Geschäftsprozessmodell zum Softwareartefakt - modellgetriebene Systementwicklung mit dem Eclipse Modeling Framework

Zur Überbrückung der semantischen Lücke zwischen der fachlichen und der softwaretechnischen Ebene in der Systementwicklung schlägt diese Arbeit einen modellgetriebenen Ansatz ausgehend von Geschäftsprozessen hin zur Generierung von Quellcode für eine service-orientierte JavaEE-Architektur vor. Der Ansatz und ein implementiertes Software-Werkzeug nutzen das Eclipse Modeling Framework (EMF) anhand von Ecore-Modellen und QVTo-basierten Modelltransformationen. Service-orientierte Anwendungssysteme werden anhand einer Xtext- und ANTLR-basierten Grammatik beschrieben, die eine auf konzeptuellen Objekttypen und Vorgangsobjekttypen (KOS und VOS der SOM-Methodik) aufbauende Syntax vorschlägt. Resultierende Ecore-Modelle sind anhand von QVTo in ein komponentenorientiertes Softwaremodell auf Basis von JavaEE überführbar. Die Transformation dieses Modells in Quellcode erzeugt ein auf einer Referenz-Architektur basierendes verteiltes Software-System bestehend aus Entitäts- und Vorgangs-Services, einschließlich JPA-Entities, SessionBeans, MessageDrivenBeans mit Message Queues und EJB-Module-Konfigurationen

Trends in Academic and Industrial Research on Business Process Management - A Computational Literature Analysis

An important aspect of enterprise information systems is the management and execution of business processes. For exploring the evolution of topics in business process management in academia and industry, we present the findings from a computational literature analysis. For this purpose, we revert to the full texts and metadata of the proceedings of the International Conference on Business Process Management and its workshops as a sample. In addition, the data has been enriched with data on the academic or industrial provenance of the authors. For identifying the most important topics in business process management, we performed a content-based analysis of over 1,200 papers using Latent Dirichlet Allocation. This analysis gives insights into the development of topics over time and identifies recently emerging topics

Multidimensional Analysis of Blockchain Data Using an ETL-based Approach

In this paper, a multidimensional model and an ETL workflow for blockchain data analysis are proposed. The workflow makes use of state-of-the-art open source tools and traditional data warehousing techniques to implement an extensible and efficient solution for the extraction, transformation, loading, and querying of data. Two scripts are implemented that aim at streamlining the ETL process, therefore simplifying the replication of the workflow to carry out a data analysis. Moreover, an exemplary use case demonstrating the analytical potential of the multidimensional model is presented and evaluated. Finally, strengths and limitations of this approach as well as the potential of future research are shown

A Comparison of Approaches for Visualizing Blockchains and Smart Contracts

The use of blockchains and smart contracts is currently explored in various fields of science and engineering due to their potential of radically changing the ways of doing business and the assumed elimination of traditional legal entities. Thereby, the complexity of the underlying technical relationships and mechanisms typically hampers the understanding by non-technical experts. In this paper we review approaches for visualizing blockchains and smart contracts. The investigation focuses on design and analysis approaches, concluding with requirements for a visual modelling language

Decentralized Business Process Modeling and Instance Tracking Secured by a Blockchain

For supporting the conceptualization and the management of enterprise models in a decentralized manner, this paper introduces an approach based on model versioning and blockchain technologies. The main contribution is twofold, consisting of a., the creation of models for inter-organizational business processes in a decentralized environment, and b., means for tracking process instances using meta-data at run time. Models for business processes, workflows, and instance states are collaboratively created as part of a decentralized architecture. Based on this approach, a hierarchical versioning and modeling approach is employed in order to create and manage public and private models in a transactional fashion. For forming relationships among decentralized participants, semi-formal models linked to a blockchain are suggested. The approach is evaluated with a supply chain use case and demonstrated in an implemented modeling tool

Past Trends and Future Prospects in Conceptual Modeling: A Bibliometric Analysis

Research in conceptual modeling is today undertaken in a large number of felds. We describe the results from a bibliometric analysis of major outlets for conceptual modeling research for investigating the evolution of research topics. As a basis for the study we used the openly accessible DBLP dataset which we enriched with data from related publisher's websites and databases. Besides a descriptive analysis of the publication data, we conducted a content-based analysis of more than 3.200 papers using Latent Dirichlet Allocation. This permits to gain insights into the past trends in conceptual modeling research and derive future prospects for the community