Abstract Executable domain-specific languages (DSLs) enable the execution of behavioral models. While an execution is mostly driven by the model content (e.g., control structures), many use cases require interacting with the running model, such as simulating scenarios in an automated or interactive way, or coupling the model with other models of the system or environment. The management of these interactions is usually hardcoded into the semantics of the DSL, which prevents its reuse for other DSLs and the provision of generic interaction-centric tools (e.g., event injector). In this paper, we propose a metalanguage for complementing the definition of executable DSLs with explicit behavioral interfaces to enable external tools to interact with executed models in a unified way. We implemented the proposed metalanguage in the GEMOC Studio and show how behavioral interfaces enable the realization of tools that are generic and thus usable for different executable DSLs.

Executable Domain-Specific Modeling Languages (xDSMLs) enable the application of early dynamic verification and validation (V&V) techniques for behavioral models. At the core of such techniques, execution traces are used to represent the evolution of models during their execution. In order to construct execution traces for any xDSML, generic trace metamodels can be used. Yet, regarding trace manipulations, generic trace metamodels lack efficiency in time because of their sequential structure, efficiency in memory because they capture superfluous data, and usability because of their conceptual gap with the considered xDSML. Our contribution is a novel generative approach that defines a multidimensional and domain-specific trace metamodel enabling the construction and manipulation of execution traces for models conforming to a given xDSML. Efficiency in time is improved by providing a variety of navigation paths within traces, while usability and memory are improved by narrowing the scope of trace metamodels to fit the considered xDSML. We evaluated our approach by generating a trace metamodel for fUML and using it for semantic differencing, which is an important V&V technique in the realm of model evolution. Results show a significant performance improvement and simplification of the semantic differencing rules as compared to the usage of a generic trace metamodel.

Code reviewing is well recognized as a valuable software engineering practice for improving software quality. Today a large variety of tools exist that support code reviewing and are widely adopted in open source and commercial software projects. They commonly support developers in manually inspecting code changes, providing feedback on and discussing these code changes, as well as tracking the review history. As source code is usually text-based, code reviewing tools also only support text-based artifacts. Hence, code changes are visualized textually and review comments are attached to text passages. This renders them unsuitable for reviewing graphical models, which are visualized graphically in diagrams instead of textually and hence require graphical change visualizations as well as annotation capabilities on the diagram level. Consequently, developers currently have to switch back and forth between code reviewing tools and comparison tools for graphical models to relate reviewer comments to model changes. Furthermore, adding and discussing reviewer comments on the diagram level is simply not possible. To improve this situation, we propose a set of coordinated visualizations of reviewing-relevant information for graphical models including model changes, diagram changes, review comments, and review history. The proposed visualizations have been implemented in a prototype tool called Mervin supporting the reviewing of graphical UML models developed with Eclipse Papyrus. Using this prototype, the proposed visualizations have been evaluated in a user study concerning effectiveness. The evaluation results show that the proposed visualizations can improve the review process of graphical models in terms of issue detection.

Computer Aided Engineering Exchange (CAEX) is one of the most promising standards when it comes to data exchange between engineering tools in the production system automation domain. This is also reflected by the current emergence of AutomationML (AML), which uses CAEX as its core representation language. However, with the increasing use of CAEX, important language engineering challenges arise. One of these challenges is the customization of CAEX for its usage in superior standards, such as AML, which requires the precise specification of the language including the formalization and validation of additional usage rules. Another highly topical challenge is the ongoing evolution of CAEX as has recently happened with the transition from version 2.15 to version 3.0. Further challenges include the provisioning of editing facilities and visualizations of CAEX documents such that they can be inspected and modified by engineers, and the development of transformations from and to CAEX such that different engineering artifacts can be exchanged via CAEX. In this paper, we take a language engineering point of view and present a model-driven engineering (MDE) workbench for CAEX that allows to address these and other challenges. In particular, we present how CAEX can be formulated in a model-based framework, which allows the application of MDE techniques, such as model validation, migration, editing, visualization, and transformation techniques, to solve a diverse set of language engineering challenges experienced for CAEX. We give an overview of the developed workbench and illustrate its benefits with a focus on customizing CAEX for AML and evolving CAEX documents from version 2.15 to 3.0.

Variability modeling is an emerging topic in the general field of systems engineering and, with current trends such as Industrie 4.0, it gains more and more interest in the domain of production systems. Therefore, it is not sufficient to describe systems in several specific cases, but instead families of systems have to be used. In this paper we introduce a role class library for AutomationML to explicitly represent variability. This allows to exchange not only system descriptions but also system family descriptions. We argue for a light-weight extension of AutomationML. The variability-based modeling approach is based on cardinalities, which is a well-known concept from conceptual modeling and feature modeling. Furthermore, we also show how instantiations of variability models can be validated by our EMF-based AutomationML workbench.

The advances of domain-specific modeling languages (DSMLs) and their editors created with modern language work-benches, have convinced domain experts of applying them as important and powerful means in their daily endeavors. Despite the fact that such editors are proficient in retaining syntactical model correctness, they present major shortages in mastering the preservation of consistency in models with elaborated language-specific constraints which require language engineers to manually implement sophisticated editing capabilities. Consequently, there is a demand for automating procedures to support editor users in both comprehending as well as resolving consistency violations. In this paper, we present an approach to automate the generation of advanced editing support for DSMLs offering automated validation, content-assist, and quick fix capabilities beyond those created by state-of-the-art language workbenches that help domain experts in retaining and achieving the consistency of models. For validation, we show potential error causes for violated constraints, instead of only the context in which constraints are violated. The state-space explosion problem is mitigated by our approach resolving constraint violations by increasing the neighborhood scope in a three-stage process, seeking constraint repair solutions presented as quick fixes to the editor user. We illustrate and provide an initial evaluation of our approach based on an Xtext-based DSML for modeling service clusters.

Reverse engineering is still a challenging process, notably because of the growing number, heterogeneity, complexity, and size of software applications. While the analysis of their structural elements has been intensively investigated, there is much less work covering the reverse engineering of their behavioral aspects. To further stimulate research on this topic, we propose fREX as an open framework for reverse engineering of executable behaviors from existing software code bases. fREX currently provides model discovery support for behavior embedded in Java code, employs the OMG's fUML standard language as executable pivot format for dynamic analysis, and uses model transformations to bridge Java and fUML. Thus, fREX also aims at contributing to explore the relationship between programming languages (e.g., Java) and executable modeling languages (e.g., fUML). In this paper, we describe the proposed fREX framework and its current reverse engineering support covering some core Java features. In addition we discuss how the framework can be used for performing different kinds of dynamic analysis on existing software, as well as how it could be extended in the future.

Data exchange is a critical issue within the multi-disciplinary engineering process of cyber physical production systems (CPPS). AutomationML (AML) is an emerging standard in the this field to represent and exchange artifacts between heterogeneous engineering tools used in mechanical, electrical, and software engineering domains. However, the interoperability of different exchange standards may be needed in order to integrate even further tools in tool chains. For instance, the Performance Model Interchange Format (PMIF) is a common representation devised in the performance engineering domain for model-based system performance analysis and simulation based on Queueing Network Models (QNM). Of course, such aspects are also of particular interest when designing a CPPS. This paper investigates, with the help of a case study, the combination of AML and PMIF as an enabling step towards an early performance validation of CPPS. By this, we close the current gap between CPPS engineering and performance engineering standards.

System models are essential in planning, designing, realizing, and maintaining production systems. AutomationML (AML) is an emerging standard to represent and exchange heterogeneous artifacts throughout the complete system life cycle and is more and more used as a modeling language. AML is designed as a flexible, prototype-based language able to represent the full spectrum of different artifacts. It may be utilized to build reusable libraries containing prototypical elements to build up production systems by using clones. However, libraries have to evolve over time, e.g., to reflect bug fixes, new features or refactorings, and so system models have to co-evolve to reflect the changes in the libraries. To tackle this co-evolution challenge, we specify in this paper the relationship between library elements, i.e., prototypes, and system elements, i.e., clones, by establishing a formal model for prototype-based modeling languages. Based on this formalization, we introduce several levels of consistency rigor one may want to achieve when modeling with prototype-based languages. These levels are also the main input to reason about the impact of library changes on the concrete system models for which we provide semi-automated co-evolution propagation strategies. We apply the established theory to the concrete AML case and present concrete tool support for evolving AML models based on Eclipse which demonstrates that consistency between system models and libraries may be maintained semi-automatically.

A multitude of Domain-Specific Languages (DSLs) have been implemented with XML Schemas. While such DSLs are well adopted and flexible, they miss modern DSL editor functionality. Moreover, since XML is primarily designed as a machine-processible format, artifacts defined with XML-based DSLs lack comprehensibility and, therefore, maintainability. In order to tackle these shortcomings, we propose a bridge between the XML Schema Definition (XSD) language and text-based metamodeling languages. This bridge exploits existing seams between the technical spaces XMLware, modelware, and grammarware as well as closes identified gaps. The resulting approach is able to generate Xtext-based editors from XSDs providing powerful editor functionality, customization options for the textual concrete syntax style, and round-trip transformations enabling the exchange of data between the involved technical spaces. We evaluate our approach by a case study on TOSCA, which is an XML-based standard for defining Cloud deployments. The results show that our approach enables bridging XMLware with modelware and grammarware in several ways going beyond existing approaches and allows the automated generation of editors that are at least equivalent to editors manually built for XML-based languages.

Model-driven development, which has recently gained momentum in academia as well as in industry, changed the software engineering process significantly from being code-centric to being model-centric. Models are considered as the key artifacts and as a result the success of the whole software development process relies on these models and their quality. Consequently, there is an urgent need for adequate methods to ensure high quality of models. Model execution can serve as the crucial basis for such methods by enabling to automatically test and debug models. Therefore, lessons learned from testing and debugging of code may serve as a valuable source of inspiration. However, the peculiarities of models in comparison to code, such as multiple views and different abstraction levels, impede the direct adoption of existing methods for models. Thus, we claim that the currently available tool support for model testing and debugging is still insufficient because these peculiarities are not adequately addressed. In this work, we aim at tackling these shortcomings by proposing a novel model execution environment based on fUML, which enables to efficiently test and debug UML models.

When defining a domain-specific modeling language (DSML), the two key components that have to be specified are its syntax and semantics. For specifying a modeling language's abstract syntax, metamodels are the standard means. MOF provides a standardized, well established, and widely accepted metamodeling language enabling the definition of metamodels and the generation of accompanying modeling facilities. However, no such standard means exist for specifying the behavioral semantics of a DSML. This hampers the efficient development of model execution facilities, such as debugging, simulation, and verification. To overcome this limitation, we propose to integrate fUML with MOF to enable the specification of the behavioral semantics for DSMLs in terms of fUML activities. We discuss alternatives how this integration can be achieved and show by-example how to specify the semantics of a DSML using fUML. To reuse existing runtime infrastructures, we further demonstrate the usage of external libraries in fUML-based specifications.