Live modeling is the ability to change an executable model at runtime, and without having to restart its execution. Sometimes this 'breaks' the ongoing execution, but in many cases, it does not have to. In earlier work, we reduced this problem to detecting fine-grained read/write conflicts between the recorded history of edit operations (created by the user) and execution steps (created by the interpreter). In this paper, we extend our approach by adding the ability to perform model checking during live modeling sessions. We motivate that this further enhances the live modeling experience, producing counter-examples or 'witness traces' relative to the current execution state, as a possible 'future', integrated with the execution and edit history, minimizing the mental gap. The model checker itself is generic, and uses (via an adapter) the language's existing interpreter. This way, we could implement this paper's running example in a working prototype with relatively little effort.

Live modeling is the ability to edit an executable model at run-time, and to subsequently continue the execution instead of having to restart it. Few modeling frameworks support this feature. Much of the research concerning live modeling attempts to bring “liveness” to existing modeling languages and environments, which is a complex, and often ad hoc endeavor. We instead argue to build modeling environments on an operation-based versioning foundation, to not only record edit operations, but also execution steps on an explicit run-time model. This reduces the complexity of patching the run-time state with edit operations to a simple merge-operation, while getting powerful features such as collaborative editing and debugging “for free.”

The Twinning paradigm -subsuming Digital Models, Digital Shadows and Digital Twins-is a powerful enabler for analyzing, verifying, deploying and maintaining complex Cyber-Physical Systems (CPSs).Throughout the (currently quite ad-hoc) creation of such systems, a plethora of choices impacts the functionality and performance of the realized Twinning system comprised of the actual system under study and its twin.The choices that are made have a high impact on the required investment when creating the twin, most notably on the development time and deployment cost.This is especially true when multiple iterations are needed to find the most appropriate level(s) of abstraction and detail, architecture, technologies and tools.As a core contribution, this work follows a Model-Based Systems Engineering methodology: before realizing a Twinning architecture, Discrete EVent system Specification (DEVS) models for deployed architecture alternatives are constructed and simulated, to evaluate their suitability.A simple use-case of a ship moving in one dimension is used as a running example.

Digital twins (DTs) are prevalent throughout industrial domains as evidenced by the rapid pace of experience reports in the literature.However, there remains disagreement about the precise definition of a DT and the essential characteristics in the DT paradigm, such as the scope of the system-under-study and the time-scale of its communication with the DT.These experience reports could therefore be hampering further classification and research insights by not reporting all of these relevant details about the DT solutions.We address these concerns by providing a conceptual structure for DTs as a common understanding and checklist for researchers and practitioners to precisely describe the characteristics and capabilities of their DT solutions.We express five experience reports using our structure to demonstrate its applicability and role as a guideline to improve the reporting of characteristics and increase the clarity of future experience reports.

Abstract The complexity of cyber–physical systems (CPSs) is commonly addressed through complex workflows, involving models in a plethora of different formalisms, each with their own methods, techniques, and tools. Some workflow patterns, combined with particular types of formalisms and operations on models in these formalisms, are used successfully in engineering practice. To identify and reuse them, we refer to these combinations of workflow and formalism patterns as modelling paradigms. This paper proposes a unifying (Descriptive) Framework to describe these paradigms, as well as their combinations. This work is set in the context of Multi-Paradigm Modelling (MPM), which is based on the principle to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s) and workflows. The purpose of the Descriptive Framework presented in this paper is to serve as a basis to reason about these formalisms, workflows, and their combinations. One crucial part of the framework is the ability to capture the structural essence of a paradigm through the concept of a paradigmatic structure. This is illustrated informally by means of two example paradigms commonly used in CPS: Discrete Event Dynamic Systems and Synchronous Data Flow. The presented framework also identifies the need to establish whether a paradigm candidate follows, or qualifies as, a (given) paradigm. To illustrate the ability of the framework to support combining paradigms, the paper shows examples of both workflow and formalism combinations. The presented framework is intended as a basis for characterisation and classification of paradigms, as a starting point for a rigorous formalisation of the framework (allowing formal analyses), and as a foundation for MPM tool development.

In Domain-Specific Modelling (DSM) the general goal is to provide Domain-Specific Modelling Languages (DSMLs) for domain users to model systems using concepts and notations they are familiar with, in their problem domain. Verifying whether a model satisfies a set of requirements is considered to be an important challenge in DSM, but is nevertheless mostly neglected. We present a solution in the form of ProMoBox, a framework that integrates the definition and verification of temporal properties in discrete-time behavioural DSMLs, whose semantics can be described as a schedule of graph rewrite rules. Thanks to the expressiveness of graph rewriting, this covers a very large class of problems. With ProMoBox, the domain user models not only the system with a DSML, but also its properties, input model, run-time state and output trace. A DSML is thus comprised of five sublanguages, which share domain-specific syntax, and are generated from a single metamodel. Generic transformations to and from a verification backbone ensure that both the language engineer and the domain user are shielded from underlying notations and techniques. We explicitly model the ProMoBox framework's process in the paper. Furthermore, we evaluate ProMoBox to assert that it supports the specification and verification of properties in a highly flexible and automated way.

Simulation-based analyses of Cyber-Physical Systems are fundamental in industrial design and testing approaches. The utility of analyses relies on the correct configuration of the simulation tools, which can be highly complicated. System engineers can normally judge the results, and either evaluate multiple simulation algorithms, or change the models. However, this is not possible in a co-simulation approach. Co-simulation is a technique to perform full-system simulation, by combining multiple black-box simulators, each responsible for a part of the system. In this paper, we demonstrate the difficulty of correctly configuring a co-simulation scenario using an industrial case study. We propose an approach to tackle this challenge by allowing multiple engineers, specialized in different domains, to encode some of their experience in the form of hints. These hints, together with state-of-the-art best practices, are then used to semi-automatically guide the configuration process of the co-simulation. We report the application of this approach to a use case proposed by our industrial partners, and discuss some of the lessons learned.

The complexity of engineered systems is ever increasing, resulting in a plethora of larger and more diverse models. This increase in complexity can be addressed by collaborative model development, also known as Concurrent Engineering. We distinguish two distinct types of collaboration, based on the different collaboration needs between modellers: screenshare and modelshare. Screenshare allows users to collaborate-often at the same time-using exactly the same visualization. This implies that even the most trivial model modifications, even semantics-preserving ones, are replicated for all users. Modelshare allows users to share the same model, albeit with different visualizations, offering different views on the model, as standardized in ISO/IEC/IEEE 42010:2011. Both types of collaboration are currently in use. We present a unifying framework integrating both approaches. This unifying framework is similar to our existing framework for concrete syntax, reusing existing modelling tool infrastructure. This allows for different types of collaboration to be intertwined: screensharing with some users, while modelsharing with other users.

The Two-hemisphere model-driven (2HMD) approach assumes modelling and use of procedural and conceptual knowledge on an equal and related basis.This differentiates 2HMD approach from pure procedural, pure conceptual, and object oriented approaches.The approach may be applied in the context of modelling of a particular business domain as well as in the context of modelling the knowledge about the domain.Cyber-physical systems are heterogeneous systems, which require multi-disciplinary approach to their modelling.Modelling of cyber-physical systems by 2HMD approach gives an opportunity to transparently compose and analyse system components to be provided and components actually provided, and, thus, to identify and fill the gaps between desirable and actual system content.

Domain-Specific Modelling Languages (DSLs) allow domain experts to create models using abstractions they are most familiar with. A DSL's syntax is specified in two parts: the abstract syntax defines the language's concepts and their allowed combinations, and the concrete syntax defines how those concepts are presented to the user (typically using a graphical or textual notation). However important concrete syntax is for the usability of the language, current modelling tools offer limited possibilities for defining the mapping between abstract and concrete syntax. Often, the language designer is restricted to defining a single icon representation of each concept, which is then rendered to the user in a (fixed) graphical interface. This paper presents a framework that explicitly models the bi-directional mapping between the abstract and concrete syntax, thereby making these restrictions easy to overcome. It is more flexible and allows, amongst others, for a model to be represented in multiple front-ends, using multiple representation formats, and multiple mappings. Our approach is evaluated with an implementation in our prototype tool, the Modelverse, and by applying it on an example language.

Improving simulation performance using activity tracking has attracted attention in the modeling field in recent years. The reference to activity has been successfully used to predict and promote the simulation performance. Tracking activity, however, uses only the inherent performance information contained in the models. To extend activity prediction in modeling, we propose the activity enhanced modeling with an activity meta-model at the meta-level. The meta-model provides a set of interfaces to model activity in a specific domain. The activity model transformation in subsequence is devised to deal with the simulation difference due to the heterogeneous activity model. Finally, the resource-aware simulation framework is implemented to integrate the activity models in activity-based simulation. The case study shows the improvement brought on by activity-based simulation using discrete event system specification (DEVS).

We propose a transformation from digital logic circuits modelled in the Logisim modelling language (and tool) to behaviourally equivalent models in the Discrete-EVent System specification (DEVS) formalism. This is achieved by mapping each Logisim component to a corresponding atomic DEVS model and by preserving the component coupling. The challenge in this work is the faithful preservation of all details of the Logisim semantics. The transformation is described and the translation of an example data path is given.

Embedded systems, with their tight technology integration, and multiple requirements and stakeholders, are characterized by tightly interrelated processes, information and tools. Embedded systems will as a consequence be described by multiple, heterogeneous and interrelated descriptions such as for example requirements documents, design and analysis models, software and hardware descriptions. We refer to a system designed this way as a multi-view (MV) system. The main contribution of this paper is a characterization of model-based approaches to MV systems. The characterization takes three main perspectives for the relations between viewpoints: semantic relations (content), relations over time (process), and manipulation of views (operations). We complement these perspectives by investigating MV system challenges and by a survey of related approaches. The characterization aims to provide a basis for a better understanding, design and implementation of MV systems, and thereby to overcome the current fragmented points of view on integrated multi-view modeling (MVM).

Domain-specific modeling (DSM) is one major building block of model-driven engineering. By moving from the solution space to the problem space, systems are designed by domain experts. The benefits of DSM are not unique to the design of systems, the specification and verification of desired properties of the designed systems by the help of DSM seems the next logical step. However, this latter aspect is often neglected by DSM approaches or only supported by translating design models to formal representations on which temporal properties are defined and evaluated. Obviously, this transition to the solution space is in contradiction with DSM.

Decision modeling is an essential part of the combat system effectiveness simulation (CoSES), which needs to cope with the cognitive quality, diversity, flexibility, and higher abstraction of decision making. In this paper, a multi-paradigm decision modeling framework is proposed to support decision modeling at three levels of abstraction based on domain-specific modeling (DSM). This framework designs a domain-specific modeling language (DSML) for decision modeling to raise the abstraction level of modeling, transforms the domain-specific models to formalism-based models to enable formal analysis and early verification and validation, and implements the semantics of the DSML based on a Python scripts framework which incorporates the decision model into the whole simulation system. The case study shows that the proposed approach incorporates domain expertise and facilitates domain modeler’s participation in CoSES to formulate the problem using DSML in the problem domain, and enables formal analysis and automatic implementation of the decision model in the solution domain.

In Model Driven Engineering (MDE), models are first-class citizens, and model transformation is MDE's "heart and soul". Since model transformations are executed for a family of conforming models, their validity becomes a crucial issue. This paper proposes to explore the question of the formal verification of model transformation properties through a tri-dimensional approach: the transformation involved, the properties of interest addressed, and the formal verification techniques used to establish the properties. This work allows a better understanding of the expected properties for a particular transformation, and facilitates the identification of the suitable tools and techniques for enabling their verification.

Domain-specific modelling (DSM) enables experts of arbitrary domains to perform modelling tasks using familiar constructs. This contrasts with common code-centric development approaches where programmers deal with object-oriented approximations of higher level concepts. Domain-specific concepts and their relationships are captured by domain-specific languages (DSLs). Unfortunately, it is common practice for DSLs to be specified within the object-oriented mindsets of classes and associations. This approach not only contradicts the model-driven engineering (MDE) philosophy of development using domain-specific concepts -- in this case, the domain and concepts of DSLs --, it is also faced with the same obstacle as past UML-to-code generation efforts; namely, that UML models are too generic to enable complete program synthesis. In the context of DSL engineering, this obstacle translates to the necessity for DSL designers to explicitly define DSL semantics manually (e.g., via coded generators and/or model transformations). In this work, we propose a novel approach to DSL design where low level modelling formalisms are seamlessly woven together to form new DSLs whose semantics are fully automatically generated.

Abstract We present a novel approach for the automatic generation of model-to-model transformations given a description of the operational semantics of the source language in the form of graph transformation rules. The approach is geared to the generation of transformations from Domain-Specific Visual Languages (DSVLs) into semantic domains with an explicit notion of transition, like for example Petri nets. The generated transformation is expressed in the form of operational triple graph grammar rules that transform the static information (initial model) and the dynamics (source rules and their execution control structure). We illustrate these techniques with a DSVL in the domain of production systems, for which we generate a transformation into Petri nets. We also tackle the description of timing aspects in graph transformation rules, and its analysis through their automatic translation into Time Petri nets.

Recent research has focused on extending standard requirements elicitation processes to address potential abnormal situations that can interrupt normal system interaction at run-time. We proposed a process, DREP, that extends use case-driven modelling with elements that allow the modelling of system behaviour in exceptional situations. This paper discusses the challenge of using the notions of exceptional behaviour and outcomes defined in use cases within a MDE process. In order to create a more formal specification model with activity diagrams, the use cases have to be well-formed to begin with. We describe precise transformation rules to systematically create an activity diagram corresponding to each use case. Special stereotypes are introduced to document partial or degraded outcomes and handling activities. The model resulting from the transformation unambiguously specifies the system interactions required to satisfy the user, as well as exceptional interactions that can lead to degraded service provision.