arXiv subjects

Andreas Wortmann

Publications and source records attributed to Andreas Wortmann.

At least 19 recordsLinked to original sources

arXiv2026

Software-heavy Asset Administration Shells: Classification and Use Cases

The Asset Administration Shell (AAS) is an emerging technology for the implementation of digital twins in the field of manufacturing. Software is becoming increasingly important, not only in general but specifically in relation to manufacturing, especially with regard to digital manufacturing and a shift towards the usage of artificial intelligence. This increases the need not only to model software, but also to integrate services directly into the AAS. The existing literature contains individual solutions to implement such software-heavy AAS. However, there is no systematic analysis of software architectures that integrate software services directly into the AAS. This paper aims to fill this research gap and differentiate architectures based on software quality criteria as well as typical manufacturing use cases. This work may be considered as an interpretation guideline for software-heavy AAS, both in academia and for practitioners.

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arXiv2026

Industrial Semantics-Aware Digital Twins: A Hybrid Graph Matching Approach for Asset Administration Shells

Although the Asset Administration Shell (AAS) standard provides a structured and machine-readable representation of industrial assets, their semantic comparability remains a major challenge, particularly when different vocabularies and modeling practices are used. Engineering would benefit from retrieving existing AAS models that are similar to the target in order to reuse submodels, parameters, and metadata. In practice, however, heterogeneous vocabularies and divergent modeling conventions hinder automated, content-level comparison across AAS. This paper proposes a hybrid graph matching approach to enable semantics-aware comparison of Digital Twin representations. The method combines rule-based pre-filtering using SPARQL with embedding-based similarity calculation leveraging RDF2vec to capture both structural and semantic relationships between AAS models. This contribution provides a foundation for enhanced discovery, reuse, and automated configuration in Digital Twin networks.

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arXiv2025

A Container-based Approach For Proactive Asset Administration Shell Digital Twins

In manufacturing, digital twins, realized as Asset Administration Shells (AAS), have emerged as a prevalent practice. These digital replicas, often utilized as structured repositories of asset-related data, facilitate interoperability across diverse systems. However, extant approaches treat the AAS as a static information model, lacking support for dynamic service integration and system adaptation. The existing body of literature has not yet thoroughly explored the potential for integrating executable behavior, particularly in the form of containerized services, into or from the AAS. This integration could serve to enable proactive functionality. In this paper, we propose a submodel-based architecture that introduces a structured service notion to the AAS, enabling services to dynamically interact with and adapt AAS instances at runtime. This concept is implemented through the extension of a submodel with behavioral definitions, resulting in a modular event-driven architecture capable of deploying containerized services based on embedded trigger conditions. The approach is illustrated through a case study on a 3-axis milling machine. Our contribution enables the AAS to serve not only as a passive digital representation but also as an active interface for executing added-value services.%, thereby laying the foundation for future AI-driven adaptation and system-level intelligence in digital twin environments.

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arXiv2025

Declarative Policy Control for Data Spaces: A DSL-Based Approach for Manufacturing-X

The growing adoption of federated data spaces, such as in the GAIA-X and the International Data Spaces (IDS) initiative, promises secure and sovereign data sharing across organizational boundaries in Industry 4.0. In manufacturing ecosystems, this enables use cases, such as cross-factory process optimization, predictive maintenance, and supplier integration. Frameworks and standards, such as the Asset Administration Shell (AAS), Eclipse Dataspace Connector (EDC), ID-Link and Open Platform Communications Unified Architecture (OPC UA) provide a strong foundation to realize this ecosystem. However, a major open challenge is the practical description and enforcement of context-dependent data usage policies using these base technologies - especially by domain experts without software engineering backgrounds. Therefore, this article proposes a method for leveraging domain-specific languages (DSLs) to enable declarative, human-readable, and machine-executable policy definitions for sovereign data sharing via data space connectors. The DSL empowers domain experts to specify fine-grained data governance requirements - such as restricting access to data from specific production batches or enforcing automatic deletion after a defined retention period - without writing imperative code.

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arXiv2025

Digital Twins for Software Engineering Processes

Digital twins promise a better understanding and use of complex systems. To this end, they represent these systems at their runtime and may interact with them to control their processes. Software engineering is a wicked challenge in which stakeholders from many domains collaborate to produce software artifacts together. In the presence of skilled software engineer shortage, our vision is to leverage DTs as means for better rep- resenting, understanding, and optimizing software engineering processes to (i) enable software experts making the best use of their time and (ii) support domain experts in producing high-quality software. This paper outlines why this would be beneficial, what such a digital twin could look like, and what is missing for realizing and deploying software engineering digital twins.

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arXiv2025

Towards a Unifying Reference Model for Digital Twins of Cyber-Physical Systems

Digital twins are sophisticated software systems for the representation, monitoring, and control of cyber-physical systems, including automotive, avionics, smart manufacturing, and many more. Existing definitions and reference models of digital twins are overly abstract, impeding their comprehensive understanding and implementation guidance. Consequently, a significant gap emerges between abstract concepts and their industrial implementations. We analyze popular reference models for digital twins and combine these into a significantly detailed unifying reference model for digital twins that reduces the concept-implementation gap to facilitate their engineering in industrial practice. This enhances the understanding of the concepts of digital twins and their relationships and guides developers to implement digital twins effectively.

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arXiv2022

Industry Best Practices in Robotics Software Engineering

Robotics software is pushing the limits of software engineering practice. The 3rd International Workshop on Robotics Software Engineering held a panel on "the best practices for robotic software engineering". This article shares the key takeaways that emerged from the discussion among the panelists and the workshop, ranging from architecting practices at the NASA/Caltech Jet Propulsion Laboratory, model-driven development at Bosch, development and testing of autonomous driving systems at Waymo, and testing of robotics software at XITASO. Researchers and practitioners can build on the contents of this paper to gain a fresh perspective on their activities and focus on the most pressing practices and challenges in developing robotics software today.

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arXiv2021

Design Thinking and Creativity of Co-located vs. Globally Distributed Software Developers

Context: Designing software is an activity in which software developers think and make design decisions that shape the structure and behavior of software products. Designing software is one of the least understood software engineering activities. In a collaborative design setting, various types of distances can lead to challenges and effects that potentially affect how software is designed. Objective: To contribute to a better understanding of collaborative software design, we investigate how geographic distance affects its design thinking and the creativity of its discussions. Method: To this end, we conducted a multiple-case study exploring the design thinking and creativity of co-located and distributed software developers in a collaborative design setting. Results: Compared to co-located developers, distributed developers spend less time on exploring the problem space, which could be related to different socio-technical challenges, such as lack of awareness and common understanding. Distributed development does not seem to affect the creativity of their activities. Conclusion: Developers engaging in collaborative design need to be aware that problem space exploration is reduced in a distributed setting. Unless distributed teams take compensatory measures, this could adversely affect the development. Regarding the effect distance has on creativity, our results are inconclusive and further studies are needed.

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arXiv2021

Self-Adaptive Manufacturing with Digital Twins

Digital Twins are part of the vision of Industry 4.0 to represent, control, predict, and optimize the behavior of Cyber-Physical Production Systems (CPPSs). These CPPSs are long-living complex systems deployed to and configured for diverse environments. Due to specific deployment, configuration, wear and tear, or other environmental effects, their behavior might diverge from the intended behavior over time. Properly adapting the configuration of CPPSs then relies on the expertise of human operators. Digital Twins (DTs) that reify this expertise and learn from it to address unforeseen challenges can significantly facilitate self-adaptive manufacturing where experience is very specific and, hence, insufficient to employ deep learning techniques. We leverage the explicit modeling of domain expertise through case-based reasoning to improve the capabilities of Digital Twins for adapting to such situations. To this effect, we present a modeling framework for self-adaptive manufacturing that supports modeling domain-specific cases, describing rules for case similarity and case-based reasoning within a modular Digital Twin. Automatically configuring Digital Twins based on explicitly modeled domain expertise can improve manufacturing times, reduce wastage, and, ultimately, contribute to better sustainable manufacturing.

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arXiv2021

Towards a Systematic Engineering of Industrial Domain-Specific Language

Domain-Specific Languages (DSLs) help practitioners in contributing solutions to challenges of specific domains. The efficient development of user-friendly DSLs suitable for industrial practitioners with little expertise in modelling still is challenging. For such practitioners, who often do not model on a daily basis, there is a need to foster reduction of repetitive modelling tasks and providing simplified visual representations of DSL parts. For industrial language engineers, there is no methodical support for providing such guidelines or documentation as part of reusable language modules. Previous research either addresses the reuse of languages or guidelines for modelling. For the efficient industrial deployment of DSLs, their combination is essential: the efficient engineering of DSLs from reusable modules that feature integrated documentation and guidelines for industrial practitioners. To solve these challenges, we propose a systematic approach for the industrial engineering of DSLs based on the concept of reusable DSL Building Blocks, which rests on several years of experience in the industrial engineering of DSLs and their deployment to various organizations. We investigated our approach via focus group methods consisting of five participants from industry and research qualitatively. Ultimately, DSL Building Blocks support industrial language engineers in developing better usable DSLs and industrial practitioners in more efficiently achieving their modelling.

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arXiv2019

Towards Self-Explainable Cyber-Physical Systems

With the increasing complexity of CPSs, their behavior and decisions become increasingly difficult to understand and comprehend for users and other stakeholders. Our vision is to build self-explainable systems that can, at run-time, answer questions about the system's past, current, and future behavior. As hitherto no design methodology or reference framework exists for building such systems, we propose the MAB-EX framework for building self-explainable systems that leverage requirements- and explainability models at run-time. The basic idea of MAB-EX is to first Monitor and Analyze a certain behavior of a system, then Build an explanation from explanation models and convey this EXplanation in a suitable way to a stakeholder. We also take into account that new explanations can be learned, by updating the explanation models, should new and yet un-explainable behavior be detected by the system.

cs.AI↗

arXiv2016

Modeling Variability in Template-based Code Generators for Product Line Engineering

Generating software from abstract models is a prime activity in model-drivenengineering. Adaptable and extendable code generators are important to address changing technologies as well as user needs. However, theyare less established, as variability is often designed as configuration options of monolithic systems. Thus, code generation is often tied to a fixed set of features, hardly reusable in different contexts, and without means for configuration of variants. In this paper,we present an approach for developing product lines of template-based code generators. This approach applies concepts from feature-oriented programming to make variability explicit and manageable. Moreover, it relies on explicit variability regions (VR) in a code generators templates, refinements of VRs, and the aggregation of templates and refinements into reusable layers. Aconcrete product is defined by selecting one or multiple layers. If necessary, additional layers required due to VR refinements are automatically selected.

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arXiv2016

Modeling Reusable, Platform-Independent Robot Assembly Processes

Smart factories that allow flexible production of highly individualized goods require flexible robots, usable in efficient assembly lines. Compliant robots can work safely in shared environments with domain experts, who have to program such robots easily for arbitrary tasks. We propose a new domain-specific language and toolchain for robot assembly tasks for compliant manipulators. With the LightRocks toolchain, assembly tasks are modeled on different levels of abstraction, allowing a separation of concerns between domain experts and robotics experts: externally provided, platform-independent assembly plans are instantiated by the domain experts using models of processes and tasks. Tasks are comprised of skills, which combine platform-specific action models provided by robotics experts. Thereby it supports a flexible production and re-use of modeling artifacts for various assembly processes.

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arXiv2015

Tailoring the MontiArcAutomaton Component & Connector ADL for Generative Development

Component&connector (C&C) architecture description languages (ADLs) combine component-based software engineering and model-driven engineering to increase reuse and to abstract from implementation details. Applied to robotics application development, current C&C ADLs often require domain experts to provide component behavior descriptions as programming language artifacts or as models of a-priori mixed behavior modeling languages. They are limited to specific target platforms or require extensive handcrafting to transform platform-independent software architecture models into platform-specific implementations. We have developed the MontiArcAutomaton framework that combines structural extension of C&C concepts with integration of application-specific component behavior modeling languages, seamless transformation from logical into platform-specific software architectures, and a-posteriori black-box composition of code generators for different robotics platforms. This paper describes the roles and activities for tailoring MontiArcAutomaton to application-specific demands.

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arXiv2015

Transforming Platform-Independent to Platform-Specific Component and Connector Software Architecture Models

Combining component & connector architecture descriptionlanguageswithcomponentbehaviormodelinglanguages enables modeling great parts of software architectures platformindependently. Nontrivial systems typically contain components with programming language behavior descriptions to interface with APIs. These components tie the complete software architecture to a specific platform and thus hamper reuse. Previous work on software architecture reuse with multiple platforms either requires platform-specific handcrafting or the effort of explicit platform models. We present an automated approach to transform platform-independent, logical software architectures into architectures with platform-specific components. This approach introduces abstract components to the platform-independent architecture and refines the se with components specific to the target platform prior to code generation. Consequently, a single logical software architecture model can be reused with multiple target platforms, which increases architecture maturity and reduces the maintenance effort of multiple similar software architectures.

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arXiv2015

Generating Domain-Specific Transformation Languages for Component & Connector Architecture Descriptions

Component-based software engineering (CBSE) decomposes complex systems into reusable components. Model-driven engineering (MDE) aims to abstract from complexities by lifting abstract models to primary development artifacts. Component and connector architecture description languages (ADLs) combine CBSE and MDE to describe software systems as hierarchies of component models. Using models as development artifacts is accompanied with the need to evolve, maintain and refactor those models, which can be achieved by model transformations. Domain-specific transformation languages (DSTLs) are tailored to a specific modeling language as the modeling language's concrete syntax is used to describe transformations. To automate the development of DSTLs for ADLs, we present a framework to systematically derive such languages from domain-specific C&C language grammars. These DSTLs enable to describe such model transformations concisely in vocabulary of the underlying ADL. These domain-specific transformations are better comprehensible to ADL experts than generic transformations.

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arXiv2015

A Comparison of Mechanisms for Integrating Handwritten and Generated Code for Object-Oriented Programming Languages

Code generation from models is a core activity in model-driven development (MDD). For complex systems it is usually impossible to generate the entire software system from models alone. Thus, MDD requires mechanisms for integrating generated and handwritten code. Applying such mechanisms without considering their effects can cause issues in projects with many model and code artifacts, where a sound integration for generated and handwritten code is necessary. We provide an overview of mechanisms for integrating generated and handwritten code for object-oriented languages. In addition to that, we define and apply criteria to compare these mechanisms. The results are intended to help MDD tool developers in choosing an appropriate integration mechanism.

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arXiv2015

Integration of Heterogeneous Modeling Languages via Extensible and Composable Language Components

Effective model-driven engineering of complex systems requires to appropriately describe different specific system aspects. To this end, efficient integration of different heterogeneous modeling languages is essential. Modeling language integaration is onerous and requires in-depth conceptual and technical knowledge and ef- fort. Traditional modeling lanugage integration approches require language engineers to compose monolithic language aggregates for a specific task or project. Adapting these aggregates cannot be to different contexts requires vast effort and makes these hardly reusable. This contribution presents a method for the engineering of grammar-based language components that can be independently developed, are syntactically composable, and ultimately reusable. To this end, it introduces the concepts of language aggregation, language embed- ding, and language inheritance, as well as their realization in the language workbench MontiCore. The result is a generalizable, systematic, and efficient syntax-oriented composition of languages that allows the agile employment of modeling languages efficiently tailored for individual software projects.

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