Bart Meyers

A framework for evolution of modelling languages

In model-driven engineering, evolution is inevitable over the course of the complete life cycle of complex software-intensive systems and more importantly of entire product families. Not only instance models, but also entire modelling languages are subject to change. This is in particular true for domain-specific languages, whose language constructs are tightly coupled to an application domain. The most popular approach to evolution in the modelling domain is a manual process, with tedious and error-prone migration of artefacts such as instance models as a result. This paper provides a taxonomy for evolution of modelling languages and discusses the different evolution scenarios for various kinds of modelling artefacts, such as instance models, meta-models, and transformation models. Subsequently, the consequences of evolution and the required remedial actions are decomposed into primitive scenarios such that all possible evolutions can be covered exhaustively. These primitives are then used in a high-level framework for the evolution of modelling languages. We suggest that our structured approach enables the design of (semi-)automatic modelling language evolution solutions.

ProMoBox: A Framework for Generating Domain-Specific Property Languages

Specifying and verifying properties of the modelled system has been mostly neglected by domain-specific modelling (DSM) approaches. At best, this is only partially supported by translating models to formal representations on which properties are specified and evaluated based on logic-based formalisms, such as linear temporal logic. This contradicts the DSM philosophy as domain experts are usually not familiar with the logics space. To overcome this shortcoming, we propose to shift property specification and verification tasks up to the domain-specific level. The ProMoBox framework consists of (i) generic languages for modelling properties and representing verification results, (ii) a fully automated method to specialize and integrate these generic languages to a given DSM language, and (iii) a verification backbone based model checking directly plug-able to DSM environments. In its current state, ProMoBox offers the designer modelling support for defining temporal properties, and for visualizing verification results, all based on a given DSM language. We report results of applying ProMoBox to a case study of an elevator controller.

Towards domain-specific property languages: the ProMoBox approach

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. To shift the specification and verification tasks to the DSM level, we extend traditional Domain-Specific Modeling Languages (DSMLs) for design with ProMoBox, a language family comprising three DSMLs covering design, property specification, and verification results. By using ProMoBox, temporal properties can be described for finite-state systems and verified by the SPIN model checker, by compiling them to Promela and Linear Temporal Logic (LTL). For specifying properties we present a DSML that is based on Dwyers specification patterns and mash it up with adapted versions of the design DSML to formulate structural patterns. In particular, we show that a ProMoBox can be generated from a single root meta-model and we demonstrate our approach with a ProMoBox for statecharts.

Composing textual modelling languages in practice

Complex systems require descriptions using multiple modelling languages, or languages able to express different concerns, like timing or data dependencies. In this paper, we propose techniques for the modular definition and composition of languages, including their abstract, concrete syntax and semantics. These techniques are based on (meta-)model templates, where interface elements and requirements for their connection can be established. We illustrate the ideas using the MetaDepth textual meta-modelling tool.

Towards an aspect-oriented language module: aspects for petri nets

The concept of composing a (domain-specific) language from different reusable modules has gained much interest over the years. The addition of aspect-oriented features to a language is a suitable candidate of such a module. However, rather than directly attempting to design an aspect-oriented language module that is applicable to any base language, this paper focuses on adding aspect-oriented features to a language that is quite different from prevalent base languages (e.g. Java): Petri nets. A running example demonstrates the use of aspects to enforce an invariant on a base Petri net.

Automated testing support for reactive domain-specific modelling languages

Domain-specific modelling languages (DSML) enable domain users to model systems in their problem domain, using concepts and notations they are familiar with. The process of domain-specific modelling (DSM) consists of two stages: a language engineering stage where a DSML is created, and a system modelling stage where the DSML is used. Because techniques such as metamodelling and model transformation allow for a efficient creation of DSMLs, and using DSMLs significantly increases productivity, DSM is very suitable for early prototyping. Many systems that are modelled using DSMLs are reactive, meaning that during their execution, they respond to external input. Because of the complexity of input and response behaviour of reactive systems, it is desirable to test models as early as possible. However, while dedicated testing support for specific DSMLs has been provided, no systematic support exists for testing DSML models according to DSM principles. In this paper, we introduce a technique to automatically generate a domain-specific testing framework from an annotated DSML definition. In our approach, the DSML definition consists of a metamodel, a concrete syntax definition and operational semantics described as a schedule of graph rewrite rules, thus covering a large class of DSMLs. Currently, DSMLs with deterministic behaviour are supported, but we provide an outlook to other (nondeterministic, real-time or continuous-time) DSMLs. We illustrate the approach with a DSML for describing an elevator controller. We evaluate the approach and conclude that compared to the state-of-the-art, our testing support is significantly less costly, and similar or better (according to DSM principles) testing support is achieved. Additionally, the generative nature of the approach makes testing support for DSMLs less error-prone while catering the need for early testing.

Concrete syntax: a multi-paradigm modelling approach

Domain-Specific Modelling Languages (DSLs) allow domain experts to create models using abstractions they are most familiar with. A DSLs syntax is specified in two parts: the abstract syntax defines the languages 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.

Domain-Specific Modelling for Human–Computer Interaction

Model-driven engineering (MDE) is an important enabler in the development of complex, reactive, often real-time, and software-intensive systems, as it shifts the level of specification from computing concepts (the “how”) to conceptual models or abstractions in the problem domain (the “what”). Domain-specific modelling (DSM) in particular allows to specify these models in a domain-specific modelling language (DSML), using concepts and notations of a specific domain. It allows the use of a custom visual syntax which is closer to the problem domain and therefore more intuitive. Models created in DSMLs are used, among others, for simulation, (formal) analysis, documentation, and code synthesis for different platforms. The goal is to enable domain experts, such as a power plant engineer, to develop, to understand, and to verify models more easily, without having to use concepts outside of their own domain. The first step in the DSM approach when modelling in a new domain is, after a domain analysis, creating an appropriate DSML. In this chapter, we give an introduction to DSML engineering and show how it can be used to develop a human–computer interaction interface. A DSML is fully defined by its syntax and semantics. The syntax consists of (i) the abstract syntax, defining the DSML constructs and their allowed combinations, captured in a metamodel, and (ii) the concrete syntax, specifying the visual representation of the different constructs. The semantics defines the meaning of models created in the domain. In this chapter, we show how two types of semantics (operational and translational) can be modelled using model transformations. Operational semantics gives meaning to the modelling language by continuously updating the model’s state, effectively building a simulator. Translational semantics defines mappings of models in one language onto models in a language with known semantics. This enables the automatic construction of behavioural models, as well as models for verification. The former can be used for automated code synthesis (leading to a running application), whereas the latter leads to model checking. We choose to specify properties for model checking using the ProMoBox approach, which allows the modelling of properties in a syntax similar to the original DSML. A major advantage of this approach is that the modeller specifies both requirements (in the form of properties) and design models in a familiar notation. The properties modelled in this domain-specific syntax are verified by mapping them to lower-level languages, such as Promela, and results are mapped back to the domain-specific level. To illustrate the approach, we create a DSML for modelling the human–computer interaction interface of a nuclear power plant.

Intensional changes avoid co-evolution!

Modularization is key to support the maintainability of software systems. In some cases, however, maintenance requires certain modules to evolve together. This phenomenon complicates software maintainability and is commonly referred to as co-evolution. In this paper, we tackle co-evolution in the domain of change-based feature-oriented programming (ChOP). In ChOP, feature modules -- each matching the implementation of one requirement -- are specified as sets of first-class change objects. Our solution is based on intensional changes: descriptive changes that are automatically evaluated with respect to the other feature modules before they are applied. We present a maintenance scenario and use it to show how intensional changes avoid co-evolution.

Semantic adaptation for FMI co-simulation with hierarchical simulators

Model-based design can shorten the development time of complex systems by the use of simulation techniques. However, it can be hard to simulate the system as a whole if it is developed in a concurrent fashion by multiple and specialized teams. Co-simulation, with the support of the Functional Mockup Interface (FMI) Standard, is proposed as a way to promote tool interoperability while protecting the intellectual property of subsystems. The standard allows uniform communication between subsystem simulators, but does not state how the inputs and outputs should be interpreted, nor how the subsystems should interact correctly. Semantic adaptations can be quickly made to correct the interactions with subsystem simulators that were produced with different assumptions, and avoid changing those subsystems, their simulators, or the orchestration algorithm that computes the co-simulation. In this work, we explore how to describe common adaptations and what their meaning is in the context of FMI co-simulation. The result is a sound language that enables the implementation of adaptations with minimal effort. A distinct feature is that it describes adaptations for groups of interconnected subsystem simulators in the same way as for a single simulator, and the implementation is itself a simulator, thanks to a sound definition of hierarchical co-simulation. This work paves the way for research into the correct combination and interfacing of different adaptations.