The reusability of modular, embeddable components is a key determinant for the success of modern programming languages to ensure efficient and high-quality development. However, there is a gap in the field of domain-specific modeling regarding reusable components at the model level. While libraries are relatively common and a de facto standard for prominent programming languages, establishing model libraries is still in its infancy. This paper specifies building a model-driven component library that utilizes a self-extension mechanism. We demonstrate an approach to structure, build, and integrate such a library using a wide range of GUI components, from essential atomic elements and more complex composed components to specifically tailored ones for particular application domains. Employing such libraries at the model level further supports the goal of model-driven engineering to assist domain experts in efficiently building high-quality systems.

In software language engineering, composition and modular design are essential milestones to advance reuse in this domain. Although language engineering improves quality and development efficiency by incorporating reusable components and tooling, some disadvantages and limitations can inhibit sophisticated language development. Current research usually focuses on the conceptual advantages but neglects the often technical drawbacks resulting from the necessity for complex interactions for seamless integration. In this paper, we report on our experiences applying language composition with the language workbench MontiCore and elaborate on the conceptual and technical drawbacks of the intended compositional tooling. Using concise application examples, we demonstrate the challenges of a compositional parser, the complexity of the generated infrastructure, and how they scrape the limits of the underlying target programming languages and their compilers. This critical examination of the implications of modular language construction demonstrates the pitfalls of language composition in the large and should reveal potential for future research.

When applying model-driven engineering in an agile environment, new requirements continuously expand the domain scope and trigger an extension of the concepts covered by the Domain-Specific Language (DSL). While programming languages streamline code extension and reuse through libraries, similar approaches for DSLs are more complex or target a specific language. We present and discuss an approach for designing DSLs with a self-extension mechanism to enable model library creation and seamless reuse. We use the self-extension mechanism to introduce concepts in models, gather reusable models into a library, and provide an infrastructure for its usage. We explain our language-specific realization of the self-extension mechanism using a DSL and discuss model libraries of the DSL with a use case from practice. The approach provides more flexibility for agile model-driven engineering. It enables application modelers to introduce and reuse concepts via models without changing the DSL, reducing the communication overhead within the development team.

In modern systems engineering, domain experts increasingly utilize models to define domain-specific viewpoints in a highly interdisciplinary context. Despite considerable advances in developing model composition techniques, their integration in a largely heterogeneous language landscape still poses a challenge. Until now, composition in practice mainly focuses on developing foundational language components or applying language composition in smaller scenarios, while the application to extensive, heterogeneous languages is still missing. In this paper, we report on our experiences of composing sophisticated modeling languages using different techniques simultaneously in the context of heterogeneous application areas such as assistive systems and cyber-physical systems in the Internet of Things. We apply state-of-the-art practices, show their realization, and discuss which techniques are suitable for particular modeling scenarios. Pushing model composition to the next level by integrating complex, heterogeneous languages is essential for establishing modeling languages for highly interdisciplinary development teams.

In Software Language Engineering, the composition of heterogeneous languages has become an increasingly relevant research area in recent years. Despite considerable advances in different composition techniques, they mainly focus on composing concrete and abstract syntax, while a thorough yet general concept for synchronizing code generators and their produced artifacts is still missing. Current solutions are either highly generic, typically increasing the complexity beyond their actual value, or strictly limited to specific applications. In this paper, we present a concept for lightweight generator composition, using the symbol tables of heterogeneous modeling languages to exchange generator-specific accessor and mutator information. The information is attached to the symbols of model elements via templates allowing code generators to communicate access routines at the code level without a further contract. Providing suitable synchronization techniques for code generation is essential to enable language composition in all aspects.

The current challenges of industrial manufacturing forces producers to optimize and to digitize their facilities. The Digital Twin as a digital representation of both the product and the production is a key enabler to efficiency, flexibility, and sustainability. Unfortunately, the development of Digital Twins is sophisticated and hampered by manual tasks. This paper presents an approach to automatically create digital models of the objects which are to be represented, based on 3D CAD data. Therefore, the CAD data, which is stored as a STEP file, is analysed to extract relevant information for the following graph analysis, which is used to identify components, their dependencies and the resulting functional modules. The graph analysis results will be used in future work to implement a digital twin.

Model-driven systems engineering relies on software languages that support different stakeholders. These languages often operate in different technological spaces. Checking consistency, tracing, and change propagation of models developed by different stakeholders, thus demands methods to bridge the gaps between these spaces. Research on the integration of heterogeneous software languages often considers heterogeneity within specific technological spaces only. We outline a systematic method to translate grammars between the technological spaces of the MontiCore and Xtext language workbench (LWB) and report observations on general grammar translation challenges. We have realized this translation in an automated toolchain and present lessons learned along the way. This can significantly facilitate bridging different technological spaces and, thus, improve model-driven systems engineering

There is a software language engineering gap between metamodel-based languages and grammar-based languages. Grammars can support integrated definition of concrete syntax and abstract syntax, which facilitates processing models, but usually prevents reusing the variety of language tools operating on Ecore metamodels (such as editors, interpreters, debuggers, etc.). Existing work on translating grammars to Ecore metamodels features very cursory translations only, which requires re-engineering intricacies natural to grammars for the metamodels again. We conceived a translation from an EBNF-like syntax to Ecore metamodels that considers the grammars’ intricacies. This translation is realized as a fully automated toolchain from grammars into Ecore & OCL using the language workbench MontiCore. Using this translation enables grammar-based languages to leverage the benefits of Ecore-compatible language tools while supporting natural definition of concrete and abstract syntax.