Juri Di Rocco

Collaborative Repositories in Model-Driven Engineering

Recently proposed model repositories aim to support specific needs--for example, collaborative modeling, the ability to use different modeling tools in software life-cycle management, tool interoperability, increased model reuse, and the integration of heterogeneous models.

Mining metrics for understanding metamodel characteristics

Metamodels are a key concept in Model-Driven Engineering. Any artifact in a modeling ecosystem has to be defined in accordance to a metamodel prescribing its main qualities. Hence, understanding common characteristics of metamodels, how they evolve over time, and what is the impact of metamodel changes throughout the modeling ecosystem is of great relevance. Similarly to software, metrics can be used to obtain objective, transparent, and reproducible measurements on metamodels too. In this paper, we present an approach to understand structural characteristics of metamodels. A number of metrics are used to quantify and measure metamodels and cross-link different aspects in order to provide additional information about how metamodel characteristics are related. The approach is applied on repositories consisting of more than 450 metamodels.

Automated Clustering of Metamodel Repositories

Over the last years, several model repositories have been proposed in response to the need of the MDE community for advanced systems supporting the reuse of modeling artifacts. Modelers can interact with MDE repositories with different intents ranging from merely repository browsing, to searching specific artifacts satisfying precise requirements. The organization and browsing facilities provided by current repositories is limited since they do not produce structured overviews of the contained artifacts, and the ategorization mechanisms (if any) are based on manual activities. When dealing with large numbers of modeling artifacts, such limitations increase the effort for managing and reusing artifacts stored in model repositories. By focusing on metamodel repositories, in this paper we propose the application of clustering techniques to automatically organize stored metamodels and to provide users with overviews of the application domains covered by the available metamodels. The approach has been implemented in the MDEForge repository.

Bridging state-based differencing and co-evolution

In Model-Driven Engineering, metamodel evolution comes with the urge of adapting those artifacts which are compromised by the changes. The existing adaptation techniques focus only on specific categories of artifacts, e.g., models or transformations. Thus, the modeler needs to become familiar with many techniques, each for different kind of artifact. To address this issue we have proposed EMF Migrate, a language devoted to the co-evolution of metamodel-based artifacts. An adaptation program written with EMF Migrate is capable of adapting artifacts (regardless of their type) according to metamodel differences calculated by means of EMF Compare. This paper addresses the problem of the compositional mismatch between EMF Compare and EMF Migrate. In particular, the differences are translated into a number of intermediate notations before being processed by an EMF Migrate adaptation program.

Traceability visualization in metamodel change impact detection

In Model-Driven Engineering metamodels are typically at the core of an ecosystem of artifacts assembled for a shared purpose. Therefore, modifying a metamodel requires care and skill as it might compromise the integrity of the ecosystem. Any change in the metamodel cannot prescind from recovering the ecosystem validity. However this has been proven to be intrinsically difficult, error-prone, and labour-intensive. This paper discusses how to generate and visualize traceability information about the dependencies between artifacts in a ecosystem and their related metamodel. Being able to understand how and where changes affect the ecosystem by means of intuitive and straightforward visualization techniques can help the modeler in deciding whether the changes are sustainable or not at an early stage of the modification process.

Models of OSS project meta-information: a dataset of three forges

The process of selecting open-source software (OSS) for adoption is not straightforward as it involves exploring various sources of information to determine the quality, maturity, activity, and user support of each project. In the context of the OSSMETER project, we have developed a forge-agnostic metamodel that captures the meta-information common to all OSS projects. We specialise this metamodel for popular OSS forges in order to capture forge-specific meta-information. In this paper we present a dataset conforming to these metamodels for over 500,000 OSS projects hosted on three popular OSS forges: Eclipse, SourceForge, and GitHub. The dataset enables different kinds of automatic analysis and supports objective comparisons of cross-forge OSS alternatives with respect to a users needs and quality requirements.

Reusing Model Transformations Through Typing Requirements Models

Model transformations are key elements of Model-Driven Engineering MDE, where they are used to automate the manipulation of models. However, they are typed with respect to concrete source and target meta-models and hence their reuse for other even similar meta-models becomes challenging. In this paper, we describe a method to extract a typing requirements model TRM from an ATL model-to-model transformation. A TRM describes the requirements that the transformation needs from the source and target meta-models in order to obtain a transformation with a syntactically correct typing. A TRM is made of three parts, two of them describing the requirements for the source and target meta-models, and the last expressing dependencies between both. We define a notion of conformance of meta-model pairs with respect to TRMs. This way, the transformation can be used with any meta-model conforming to the TRM. We present tool support and an experimental validation of correctness and completeness using meta-model mutation techniques, obtaining promising results.

Using ATL Transformation Services in the MDEForge Collaborative Modeling Platform

In the last years, the increasing complexity of Model-Driven Engineering MDE tools and techniques has led to higher demands in terms of computation, interoperability, and configuration management. Harnessing the software-as-a-service SaaS paradigm and shifting applications from local, mono-core implementations to cloud-based architectures is key to enhance scalability and flexibility. To this end, we propose MDEForge: an extensible, collaborative modeling platform that provides remote model management facilities and prevents the user from focussing on time-consuming, and less creative procedures. This demo paper illustrates the extensibility of MDEForge by integrating ATL services for the remote execution, automated testing, and static analysis of ATL transformations. The usefulness of their employment under the SaaS paradigm is demonstrated with a case-study showing a wide range of new application possibilities.

Supporting users to manage breaking and unresolvable changes in coupled evolution

In Model-Driven Engineering (MDE) metamodels play a key role since they underpin the specification of different kinds of modeling artifacts, and the development of a wide range of model management tools. Consequently, when a metamodel is changed modelers and developers have to deal with the induced coupled evolutions i.e., adapting all those artifacts that might have been affected by the operated metamodel changes. Over the last years, several approaches have been proposed to deal with the coupled evolution problem, even though the treatment of changes is still a time consuming and error-prone activity. In this paper we propose an approach supporting users during the adaptation steps that cannot be fully automated.~The approach has been implemented by extending the EMFMigrate language and by exploiting the user input facility of the Epsilon Object Language. The approach has been applied to cope with the coupled evolution of metamodels and model-to-text transformations

Systematic Recovery of MDE Technology Usage

MDE projects may use various MDE technologies (e.g., for model transformation, model comparison, or model/code generation) and thus, contain various MDE artifacts (such as models, metamodels, and model transformations). The details of using the MDE technologies and the relationships between the MDE artifacts are typically not accessible at a higher level of abstraction, which makes it hard to understand, build, and test the MDE projects and thus, to reuse the contained MDE artifacts. In this paper, we present a megamodel-based reverse engineering methodology and an infrastructure MDEprofiler for recovering details of using MDE technologies in MDE projects and modeling these details at a higher level of abstraction. We exemplify the approach for MDE projects that use ATL-based model transformations.