Model-Driven Engineering Artifacts Research Articles

Bug Localization in Model-Based Systems in the Wild

The companies that have adopted the Model-Driven Engineering (MDE) paradigm have the advantage of working at a high level of abstraction. Nevertheless, they have the disadvantage of the lack of tools available to perform bug localization at the model level. In addition, in an MDE context, a bug can be related to different MDE artefacts, such as design-time models, model transformations, or run-time models. Starting the bug localization in the wrong place or with the wrong tool can lead to a result that is unsatisfactory. We evaluate how to apply the existing model-based approaches in order to mitigate the effect of starting the localization in the wrong place. We also take into account that software engineers can refine the results at different stages. In our evaluation, we compare different combinations of the application of bug localization approaches and human refinement. The combination of our approaches plus manual refinement obtains the best results. We performed a statistical analysis to provide evidence of the significance of the results. The conclusions obtained from this evaluation are: humans have to be involved at the right time in the process (or results can even get worse), and artefact-independence can be achieved without worsening the results.

Understanding MDE projects: megamodels to the rescue for architecture recovery

Conventional wisdom on Model-Driven Engineering (MDE) suggests that this software discipline is the key to achieve superior automation, whether it be refactoring, simulation, or code generation. However, the diversity of employed languages and technologies blurs the picture making it difficult to analyze existing MDE-based projects in order to retrieve architectural information to foster a better understanding about the rationale behind them. Thus, the ability of carefully analyzing projects to identify their components and their interrelationships is key to obtain representations at a higher level of abstraction that can support reuse processes. In this paper, a megamodel-based approach to the reverse engineering of model-driven projects is proposed in order to leverage the representation of the involved technologies and assets. An automated recovery technique implemented by the MDEprofiler infrastructure is presented and illustrated by analyzing community projects in terms of basic MDE artifacts (such as models and metamodels) and the usage of common technologies such as model transformations and code generators.

Software development environments and tools in MDE

Abstract. Model-Driven Engineering (MDE) is the notion that we can construct a model of a system that we can then transform into the real thing. The development of software in MDE using Domain-Specific Languages (DSLs) has two phases. First, the development of artifacts such as DSLs and transformation mechanisms by the modeling experts. Second, people non-technical experts (domain expert or end user) using the artifacts created develop applications simply because of the high level of abstraction allowed by technology. Several factors are considered to limit the use of MDE. One of them, is the lack of knowledge the tools and the development activities with MDE. To support the MDE initiative, the present work makes a description of the theoretical foundations of MDE, also describes the main activities to build several MDE artifacts with some of the tools most known in this technology.

A Posteriori Typing for Model-Driven Engineering

Model-Driven Engineering (MDE) is founded on the ability to create and process models conforming to a meta-model. In this context, classes in a meta-model are used in two ways: as templates to create objects and as (static) classifiers for them. These two aspects are inherently tied in most meta-modelling approaches, which results in unnecessarily rigid systems and hinders reusability of MDE artefacts. In this work, we discuss the benefits of decoupling object creation from typing in MDE. Thus, we rely on standard mechanisms for object creation, and propose a posteriori typing as a means to retype objects and enable multiple, partial, dynamic typings. This approach enhances flexibility; permits unanticipated reuse, as model management operations defined for a meta-model can be reused with other models once they get reclassified; and enables bidirectional model transformation by reclassification. In particular, we propose two mechanisms to realise model retyping and show their underlying theory and analysis methods. We show the feasibility of the approach by an implementation atop our meta-modelling tool M eta D epth and present several applications of retypings (transformations, reuse, and dynamicity).

Analysis of Asset Specification Languages for Representation of Descriptive Data from MDE Artifacts

In order to improve the adoption of Model-Driven Engineering (MDE) Artifacts (e.g., design languages and associated model transformations), the literature points out that these elements need to be first shared in Knowledge Bases (KB) to be further downloaded, compared and integrated to software projects. A common concept used as pivotal representation between software artifacts and repositories is the Asset: structured information that provides standard taxonomies to catalog artifacts from different natures. In this work, we evaluated the applicability of concepts from two important asset specification languages on the representation of MDE artifacts: The Asset Management Specification (AMS) and the Reusable Asset Specification (RAS). Our contribution is a list of benefits and drawbacks from RAS and AMS to work as a pivotal language in KBs for MDE.

Evolving models in Model-Driven Engineering: State-of-the-art and future challenges

The artefacts used in Model-Driven Engineering (MDE) evolve as a matter of course: models are modified and updated as part of the engineering process; metamodels change as a result of domain analysis and standardisation efforts; and the operations applied to models change as engineering requirements change. MDE artefacts are inter-related, and simultaneously constrain each other, making evolution a challenge to manage. We discuss some of the key problems of evolution in MDE, summarise the key state-of-the-art, and look forward to new challenges in research in this area.

From types to type requirements: genericity for model-driven engineering

Model-driven engineering (MDE) is a software engineering paradigm that proposes an active use of models during the development process. This paradigm is inherently type-centric, in the sense that models and their manipulation are defined over the types of specific meta-models. This fact hinders the reuse of existing MDE artefacts with other meta-models in new contexts, even if all these meta-models share common characteristics. To increase the reuse opportunities of MDE artefacts, we propose a paradigm shift from type-centric to requirement-centric specifications by bringing genericity into models, meta-models and model management operations. For this purpose, we introduce so-called concepts gathering structural and behavioural requirements for models and meta-models. In this way, model management operations are defined over concepts, enabling the application of the operations to any meta-model satisfying the requirements imposed by the concept. Model templates rely on concepts to define suitable interfaces, hence enabling the definition of reusable model components. Finally, similar to mixin layers, templates can be defined at the meta-model level as well, to define languages in a modular way, as well as layers of functionality to be plugged-in into other meta-models. These ideas have been implemented in MetaDepth, a multi-level meta-modelling tool that integrates action languages from the Epsilon family for model management and code generation.

Guest editorial to the theme issue on traceability in model-driven engineering

This issue of Software and Systems Modeling, and part of the issue that follows, are dedicated to the theme of traceability in model-driven engineering (MDE). Traceability is a fundamental concern in MDE processes, where models are related via application of different model management operations, such as model-to-model transformations, modelto-text transformations, model merging, model comparison, and many others. MDE emphasises on the application of automated model management operations, and substantial traceability information can be produced as a side-effect of applying these operations. In addition, in realistic MDE processes, traceability information can be produced by hand, through engineers manually relate MDE artefacts, or relate MDE artefacts with other artefacts (such as requirements documents). Overall, there are many challenges to traceability in MDE, ranging from managing large traceability models, to synchronizing models, and to keep traceability information consistentwhenmodels are beingmodified automatically and manually. This theme issue presents state-ofthe-art research on these and other challenges. Since 2005, the ECMDA-FA/ECMFA Workshop on Traceability has presented the leading research on traceability in MDE. After the 2008 workshop in Berlin, authors of accepted papers from the previous four workshops were invited to submit their latest results (perhaps derived from their workshop papers) to this theme issue. At the same time, an open call was issued, soliciting submissions from the