Genericity for model management operations

Models are the core assets in model-driven engineering, and are therefore subject to all kind of manipulations, such as refactorings, animations, transformations into other languages, comparisons and merging. This set of model-related activities is known as model management. Even though many languages and approaches have been proposed for model management, most of them are type-centric, specific to concrete meta-models, and hence leading to specifications with a low level of abstraction and difficult to be reused in practice. In this paper, we introduce ideas from generic programming into model management to raise the level of abstraction of the specifications of model manipulations and facilitate their reuse. In particular we adopt generic meta-model concepts as an intermediate, abstract meta-model over which model management specifications are defined. Such meta-model concepts are mapped to concrete meta-models, so that specifications can be applied to families of meta-models satisfying the concept requirements. As a proof of concept, we show the implementation of these ideas using the Eclipse Modeling Framework and the Epsilon family of languages for model management.     

Combining unit and specification-based testing for meta-model validation and verification

Meta-models play a cornerstone role in Model-Driven Engineering as they are used to define the abstract syntax of modelling languages, and so models and all sorts of model transformations depend on them. However, there are scarce tools and methods supporting their Validation and Verification (V&V), which are essential activities for the proper engineering of meta-models.In order to fill this gap, we propose two complementary meta-model V&V languages. The first one has similar philosophy to the xUnit framework, as it enables the definition of meta-model unit test suites comprising model fragments and assertions on their (in-)correctness. The second one is directed to express and verify expected properties of a meta-model, including domain and design properties, quality criteria and platform-specific requirements.As a proof of concept, we have developed tooling for both languages in the Eclipse platform, and illustrate its use within an example-driven approach for meta-model construction. The expressiveness of our languages is demonstrated by their application to build a library of meta-model quality issues, which has been evaluated over the ATL zoo of meta-models and some OMG specifications. The results show that integrated support for meta-model V&V (as the one we propose here) is urgently needed in meta-modelling environments.     

A domain-specific language for model mutation and its application to the automated generation of exercises

Model-Driven Engineering (MDE) is a software engineering paradigm that uses models as main assets in all development phases. While many languages for model manipulation exist (e.g., for model transformation or code generation), there is a lack of frameworks to define and apply model mutations.A model mutant is a variation of an original model, created by the application of specific model mutation operations. Model mutation has many applications, for instance, in the areas of model transformation testing, model-based testing or education.In this paper, we present a domain-specific language called Wodel for the specification and generation of model mutants. Wodel is domain-independent, as it can be used to generate mutants of models conformant to arbitrary meta-models. Its development environment is extensible, permitting the incorporation of post-processors for different applications. In particular, we describe Wodel-Edu, a post-processing extension directed to the automated generation of exercises for particular domains and their automated correction. We show the application of Wodel-Edu to the generation of exercises for deterministic automata, and report on an evaluation of the quality of the generated exercises, obtaining overall good results.     

Engineering model transformations with transML

Model transformation is one of the pillars of model-driven engineering (MDE). The increasing complexity of systems and modelling languages has dramatically raised the complexity and size of model transformations as well. Even though many transformation languages and tools have been proposed in the last few years, most of them are directed to the implementation phase of transformation development. In this way, even though transformations should be built using sound engineering principles—just like any other kind of software—there is currently a lack of cohesive support for the other phases of the transformation development, like requirements, analysis, design and testing. In this paper, we propose a unified family of languages to cover the life cycle of transformation development enabling the engineering of transformations. Moreover, following an MDE approach, we provide tools to partially automate the progressive refinement of models between the different phases and the generation of code for several transformation implementation languages.     

Alliance of model-driven engineering with a proof-based formal approach

Model-driven engineering (MDE) promotes the use of models throughout the software development cycle in order to increase abstraction and reduce software complexity. It favors the definition of domain-specific modeling languages (DSMLs) thanks to frameworks dedicated to meta-modeling and code generation like EMF (Eclipse Modeling Framework). The standard semantics of meta-models allows interoperability between tools such as language analysers (e.g., XText), code generators (e.g., Acceleo), and also model transformation tools (e.g., ATL). However, a major limitation of MDE is the lack of formal reasoning tools allowing to ensure the correctness of models. Indeed, most of the verification activities offered by MDE tools are based on the verification of OCL constraints on instances of meta-models. However, these constraints mainly deal with structural properties of the model and often miss out its behavioral semantics. In this work, we propose to bridge the gap between MDE and the rigorous world of formal methods in order to guarantee the correctness of both structural and behavioral properties of the model. Our approach translates EMF meta-models into an equivalent formal B specification and then injects models into this specification. The equivalence between the resulting B specification and the original EMF model is kept by proven design steps leading to a rigorous MDE technique. The AtelierB prover is used to guarantee the correctness of the model’s behavior with respect to its invariant properties, and the ProB model-checker is used to animate underlying execution scenarios which are translated back to the initial EMF model. Besides the use of these automatic reasoning tools in MDE, proved B refinements are also investigated in this paper in order to gradually translate abstract EMF models to concrete models which can then be automatically compiled into a programming language.

     

事件和参数双因素驱动的智能模璎集成机制

为了增强DSS模型的可重用性及系统的元决策能力,提出了利用事件和参数共同驱动的双因素模型集成机制。将DSS中的可重用模型体系分解为由元模型、复合模型、过程模型构成的层次结构,重新定义了工作流管理领域中的ESP规则、元模型和复合模型的结构及通用模型接口;元模型和复合模型中的context组元利用ESP规则描述模型的应用规则,用户可通过修改ESP规则实现模型的重用和集成;在此基础上设计出以事件驱动为主和参数驱动为辅的元模型智能集成机制。以高技术虚拟企业利益分配策略优选模型的构建为例,展示了智能模型定义的方法及其集成细节。     

Model-driven engineering: A survey supported by the unified conceptual model

During the last decade a new trend of approaches has emerged, which considers models not just documentation artefacts, but also central artefacts in the software engineering field, allowing the creation or automatic execution of software systems starting from those models. These proposals have been classified generically as Model-Driven Engineering (MDE) and share common concepts and terms that need to be abstracted, discussed and understood. This paper presents a survey on MDE based on a unified conceptual model that clearly identifies and relates these essential concepts, namely the concepts of system, model, metamodel, modeling language, transformations, software platform, and software product. In addition, this paper discusses the terminologies relating MDE, MDD, MDA and others. This survey is based on earlier work, however, contrary to those, it intends to give a simple, broader and integrated view of the essential concepts and respective terminology commonly involved in the MDE, answering to key questions such as: What is a model? What is the relation between a model and a metamodel? What are the key facets of a modeling language? How can I use models in the context of a software development process? What are the relations between models and source code artefacts and software platforms? and What are the relations between MDE, MDD, MDA and other MD approaches?     

Ring: A unifying meta-model and infrastructure for Smalltalk source code analysis tools

Source code management systems record different versions of code. Tool support can then compute deltas between versions. To ease version history analysis we need adequate models to represent source code entities. Now naturally the questions of their definition, the abstractions they use, and the APIs of such models are raised, especially in the context of a reflective system which already offers a model of its own structure.We believe that this problem is due to the lack of a powerful code meta-model as well as an infrastructure. In Smalltalk, often several source code meta-models coexist: the Smalltalk reflective API coexists with the one of the Refactoring engine or distributed versioning system such as Monticello or Store. While having specific meta-models is an adequate engineered solution, it multiplies meta-models and it requires more maintenance efforts (e.g., duplication of tests, transformation between models), and more importantly hinders navigation tool reuse when meta-models do not offer polymorphic APIs.As a first step to provide an infrastructure to support history analysis, this article presents Ring, a unifying source code meta-model that can be used to support several activities and proposes a unified and layered approach to be the foundation for building an infrastructure for version and stream of change analyses. We re-implemented three tools based on Ring to show that it can be used as the underlying meta-model for remote and off-image browsing, scoping refactoring, and visualizing and analyzing changes. As a future work and based on Ring we will build a new generation of history analysis tools.     

VMTL: a language for end-user model transformation

Model transformation is a key enabling technology of Model-Driven Engineering (MDE). Existing model transformation languages are shaped by and for MDE practitioners—a user group with needs and capabilities which are not necessarily characteristic of modelers in general. Consequently, these languages are largely ill-equipped for adoption by end-user modelers in areas such as requirements engineering, business process management, or enterprise architecture. We aim to introduce a model transformation language addressing the skills and requirements of end-user modelers. With this contribution, we hope to broaden the application scope of model transformation and MDE technology in general. We discuss the profile of end-user modelers and propose a set of design guidelines for model transformation languages addressing them. We then introduce Visual Model Transformation Language (VMTL) following these guidelines. VMTL draws on our previous work on the usability-oriented Visual Model Query Language. We implement VMTL using the Henshin model transformation engine, and empirically investigate its learnability via two user experiments and a think-aloud protocol analysis. Our experiments, although conducted on computer science students exhibiting only some of the characteristics of end-user modelers, show that VMTL compares favorably in terms of learnability with two state-of the-art model transformation languages: Epsilon and Henshin. Our think-aloud protocol analysis confirms many of the design decisions adopted for VMTL, while also indicating possible improvements.     

Adapting transformations to metamodel changes via external transformation composition

Evolution is inherent to software systemsbecause of the rapid improvement of technologies and business logic. As a software development paradigm, model driven engineering (MDE) is also affected by this problem. More concretely, being metamodels the cornerstone of MDE, their evolution impacts the rest of software artefacts involved in a development process, i.e., models and transformations. The influence over models has been tackled and partially solved in previous works. This paper focuses on the impact over transformations. We propose an approach to adapt transformations by means of external transformation composition. That is, we chain impacted transformations to particular adaptation transformations which deal with either refactoring/destruction changes or construction changes. Our approach semi-automatically generates such transformations by using the AtlanMod matching language, a DSL to define model matching strategies. To provide with a proof of concept for our proposal, we adapt transformations written in terms of object-relational database metamodels when such metamodels evolve in time.     

Predicting recurring concepts on data-streams by means of a meta-model and a fuzzy similarity function

Stream-mining approach is defined as a set of cutting-edge techniques designed to process streams of data in real time, in order to extract knowledge. In the particular case of classification, stream-mining has to adapt its behavior to the volatile underlying data distributions, what has been called concept drift. It is important to note that concept drift may lead to situations where predictive models become invalid and have therefore to be updated to represent the actual concepts that data poses. In this context, there is a specific type of concept drift, known as recurrent concept drift, where the concepts represented by data have already appeared in the past. In those cases the learning process could be saved or at least minimized by applying a previously trained model.To deal with the aforementioned scenario, meta-models can be used in the process of enhancing the drift detection mechanisms used by data stream algorithms, by representing and predicting when the change will occur. There are some real-world situations where a concept reappears, as in the case of intrusion detection systems (IDS), where the same incidents or an adaptation of them usually reappear over time. In these environments the early prediction of drift by means of a better knowledge of past models can help to anticipate to the change, thus improving efficiency of the model regarding the training instances needed.Furthermore, as a complement of meta-models, a mechanism to assess the similarity between classification models is also needed when dealing with recurrent concepts. In this context, when reusing a previously trained model a rough comparison between concepts is usually made, applying boolean logic. The introduction of fuzzy logic comparisons between models could lead to a better efficient reuse of previously seen concepts, by applying not just equal models, but also similar ones.This work faces the aforementioned open issues by means of the MM-PRec system, that integrates a meta-model mechanism and a fuzzy similarity function. The theoretical proposal of MM-PRec is also validated in this paper by means of different experiments using both synthetic and real datasets.     

Grammar-based model transformations: Definition,execution, and quality properties

Model transformation is a key concept in model-driven software engineering. The definition of model transformations is usually based on meta-models describing the abstract syntax of languages. While meta-models are thereby able to abstract from superfluous details of concrete syntax, they often loose structural information inherent in languages, like information on model elements always occurring together in particular shapes. As a consequence, model transformations cannot naturally re-use language structures, thus leading to unnecessary complexity in their development as well as in quality assurance.In this paper, we propose a new approach to model transformation development which allows to simplify the developed transformations and improve their quality via the exploitation of the languages׳ structures. The approach is based on context-free graph grammars and transformations defined by pairing productions of source and target grammars. We show that such transformations have important properties: they terminate and are sound, complete, and deterministic.     

TOTEM: Reconciling multi-level modelling with standard two-level modelling

Model driven Engineering (MDE) advocates the active use of models throughout the different software development phases. In MDE, models are described using meta-models, one meta-level above. This approach effectively leaves developers with one single meta-level to create their models. However, there are scenarios where the use of multiple meta-levels results in simpler models with less accidental complexity. Hence, to simplify modelling in these cases, several multi-level modelling approaches and tools have recently emerged to increase the flexibility in modelling. While they provide advanced primitives to simplify modelling, there are possibilities to improve interoperability with mainstream two-level modelling approaches based on the Meta-Object Facility (MOF) standard of the Object Management Group (OMG), and achieve wider adoption.For this purpose, we first characterise the design space of multi-level modelling approaches using a feature model. On such a basis, we provide a detailed comparison of existing multi-level modelling tools, identifying gaps and research opportunities. As a result of this gap analysis, we propose a new approach to multi-level modelling that embeds multiple meta-levels within one meta-model (i.e., encoding objects as classes, and instantiation as inheritance), and a tool – called TOTEM – which implements these concepts. The tool capabilities and its benefits in terms of interoperability with mainstream, standard modelling frameworks are illustrated through an example, as well as with empirical and analytical evaluations.     

A Meta-Model for Model-Driven Web Development

Several model-driven development (MDD) techniques for web applications exist; these techniques use meta-models for defining transformations and designing models. In this paper, we propose a meta-model for abstract web applications that can be mapped to multiple platforms. We extend a UML-based model to support specific features of the Web and Web 2.0 as well as to establish a bridge to functional and usability requirements through use cases and user interface (UI) prototypes. The meta-model also helps avoid a common MDD-related problem caused by name-based dependencies. Finally, mappings to a number of specific web platforms are presented in order to validate the appropriateness of the meta-model as an abstract web model.     

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.     

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.     

A formalisation of the copy-modify-merge approach to version control in MDE

Models are the primary artefacts of the software development process in Model-Driven Engineering (MDE). Like other software artefacts, models undergo a complex evolution during their life cycles. Version control is one of the key techniques which enable developers to tackle this complexity. Traditional version control systems (VCS) are based on the copy-modify-merge approach which is not fully exploited in MDE since current implementations lack model-orientation. In this paper we provide a formalisation of the copy-modify-merge approach in the context of MDE. In particular, we analyse how the identification of commonalities and the calculation of differences can be defined by means of category-theoretical constructions. Moreover, we demonstrate how the properties of these constructions can be used to synchronise models and detect conflicting modifications.     

A meta-modelling framework for knowledge consistency in collaborative design

The design of complex system requires a lot of interactions between experts and then between numerous Computer Aided X software (CAX) (where X can be Design (CAD), Engineering (CAE), Manufacturing (CAM), etc.). In order to improve the consistency of the whole system design and the related data and information, knowledge crossing the expertises must be tracked and formalized regarding a shared reference. That means that instead of defining a large reference models to which each expert refers to, a light collaborative model is defined enabling to connect data from each expert model to adhoc data from other expert models, following the least commitment principle. In this topic, a new meta-model is proposed in a Model-Driven Engineering approach to manage the integration of heterogeneous experts’ knowledge models in a collaborative process. The structure of the proposed knowledge meta-model is defined taking into account the complexity of knowledge definition and the properties of its components. This meta-model is split in a meta-model of data on one hand and a Collaboration Meta-Model in the other hand, to represent the distinction between the core concepts of knowledge and additional elements serving to represent the relation between these concepts, and between concepts of heterogeneous experts’ models. The proposed meta-model is illustrated on an industrial case study to highlight the way to put it in use, and its interests to enable collaboration between experts throughout the design process.     

Rigorous identification and encoding of trace-links in model-driven engineering

Model-driven engineering (MDE) involves the construction and manipulation of many models of different kinds in an engineering process. In principle, models can be used in the product engineering lifecycle in an end-to-end manner for representing requirements, designs and implementations, and assisting in deployment and maintenance. The manipulations applied to models may be manual, but they can also be automated??for example, using model transformations, code generation, and validation. To enhance automated analysis, consistency and coherence of models used in an MDE process, it is useful to identify, establish and maintain trace-links between models. However, the breadth and scope of trace-links that can be used in MDE is substantial, and managing trace-link information can be very complex. In this paper, we contribute to managing the complexity of traceability information in MDE in two ways: firstly, we demonstrate how to identify the different kinds of trace-links that may appear in an end-to-end MDE process; secondly, we describe a rigorous approach to defining semantically rich trace-links between models, where the models themselves may be constructed using diverse modelling languages. The definition of rich trace-links allows us to use tools to maintain and analyse traceability relationships.