MDEForge: an extensible Web-based modeling platform *

Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Amleto Di Salle, Ludovico Iovino, Alfonso Pierantonio
CloudMDE, 2014, 66
Abstract. Model-Driven Engineering (MDE) refers to the systematic use of models as first class entities throughout the software development life cycle. Over the last few years, many MDE technologies have been conceived for developing domain specific modeling languages, and for supporting a wide range of model management activities. However, existing modeling platforms neglect a number of important features that if missed reduce the acceptance and the relevance of MDE in industrial contexts, e.g., the possibility to search and reuse already developed modeling artifacts, and to adopt model management tools as a service. In this paper we propose MDEForge a novel extensible Web-based modeling platform specifically conceived to foster a community-based modeling repository, which underpins the development, analysis and reuse of modeling artifacts. Moreover, it enables the adoption of model management tools as software-as-a-service that can be remotely used without overwhelming the users with intricate and error-prone installation and configuration procedures.

Describing the correlations between metamodels and transformations aspects

Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino, Alfonso Pierantonio
ceur-ws.org, 2014
Abstract. 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. One of the most important artifact is model transformation that are considered to be the heart and soul of MDE and as such advanced techniques and tools are needed for supporting the development, quality assurance, maintenance, and evolution of model transformations. Several works propose the adoption of metrics to measure quality attributes of transformation without considering any metamodel aspects. In this paper, we present an approach to understand structural characteristics of metamodels and how the model transformations depend on corresponding input and target metamodels.

Collaborative Repositories in Model-Driven Engineering

Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino, Alfonso Pierantonio
IEEE Software, vol.32, no. 3, pp. 28-34, 2015
Abstract. 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.

Qualifying chains of transformation with coverage based evaluation criteria

Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino, Alfonso Pierantonio
ceur-ws.org, 2014
Abstract. In Model-Driven Engineering (MDE) the development of complex and large transformations can benefit from the reuse of smaller ones that can be composed according to user requirements. Composing transformations is a complex problem: typically smaller transformations are discovered and selected by developers from different and heterogeneous sources. Then the identified transformations are chained by means of manual and error-prone composition processes. Based on our approach, when we propose one or more transformation chains to the user, it is difficult for him to choose one path instead of another without considering the semantic properties of a transformation. In this paper when multiple chains are proposed to the user, according to his requirements, we propose an approach to classify these suitable chains with respect to the coverage of the metamodels involved in the transformation. Based on coverage value, we are able to qualify the transformation chains with

Mining correlations of ATL model transformation and metamodel metrics

Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino, Alfonso Pierantonio
IEEE Press Piscataway, NJ, USA, 2015
Abstract. Model transformations are considered to be the “heart” and “soul” of Model Driven Engineering, and as a such, advanced techniques and tools are needed for supporting the development, quality assurance, maintenance, and evolution of model transformations. Even though model transformation developers are gaining the availability of powerful languages and tools for developing, and testing model transformations, very few techniques are available to support the understanding of transformation characteristics. In this paper, we propose a process to analyze model transformations with the aim of identifying to what extent their characteristics depend on the corresponding input and target metamodels. The process relies on a number of transformation and metamodel metrics that are calculated and properly correlated. The paper discusses the application of the approach on a corpus consisting of more than 90 ATL transformations and 70 corresponding metamodels.

A Customizable Approach for the Automated Quality Assessment of Modelling Artefacts

Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino, Alfonso Pierantonio
QUATIC 2016, 2016
Abstract.In Model-Driven Engineering (MDE) giving a precise definition of quality models, identifying which quality attributes are of interest for specific stakeholders, and how relating and aggregating together quality attributes are still open issues. The main limitations of currently available quality approaches are limited extensibility, artifact specificity, and manual assessment. This paper proposes an approach supporting the definition of custom quality models consisting of hierarchically organized quality attributes whose evaluation depends on metrics specifically conceived and applied on the modeling artifacts to be analysed. A domain specific language is proposed to specify how quality attributes and metrics have to be aggregated. An execution environment is also provided to apply the defined quality models on actual modeling artifacts so to enable their automated quality assessment. Real applications of the approach are presented by defining and applying explanatory quality models suitably conceived to assess the quality of metamodels and transformations retrieved from public repositories.

Using ATL transformation services in the MDEForge collaborative modeling platform

Juri Di Rocco, Davide Di Ruscio, Alfonso Pierantonio, Jesus Sanchez Cuadrado, Juan De Lara and Esther Guerra
ICMT, 2016
Abstract. 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.

Automated Clustering of Metamodel Repositories

Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino and Alfonso Pierantonio
CAiSE, 2016
Abstract. 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.

A Tool for Clustering Metamodel Repositories

Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino and Alfonso Pierantonio
Demonstrations and Posters at MODELS, 2015
Abstract. 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 categorization mechanisms (if any) are based on manual activities. When dealing with large numbers of modeling artifacts, such limitations increase the effort related to both managing and reusing artifacts stored in model repositories. By focusing on metamodels management, in this paper we propose a clustering tool for automatically organizing stored metamodels and provide users with repository overviews as, for instance, the application domains covered by the available metamodels. The approach has been implemented and integrated in the MDEForge repository.

Model Repositories: Will they become reality?

Francesco Basciani, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino and Alfonso Pierantonio
CloudMDE, 2015
Abstract. Over the last years, several repositories have been proposed in response to the need of the MDE community for advanced systems supporting the reuse of modeling artifacts, and the adoption of model management tools as software-as-service. Even though the potential benefits of MDE repositories are valuable, researchers and practitioners seem to prefer the management of their modeling artifacts locally and do not use yet advanced mechanisms for sharing and reusing them. This paper discusses the opportunities related to the adoption of model repositories and identify research issues that have to be addressed in order to make model repositories a reality in MDE.

Automated Chaining of Model Transformations with Incompatible Metamodels

Francesco Basciani, Davide Di Ruscio, Ludovico Iovino and Alfonso Pierantonio
MODELS, 2014
Abstract. In Model-Driven Engineering (MDE) models are first-class entities that are manipulated by means of model transformations. The development of complex and large transformations can benefit from the reuse of smaller ones that can be composed according to user requirements. Composing transformations is a complex problem: typically smaller transformations are discovered and selected by developers from different and heterogeneous sources. Then the identified transformations are chained by means of manual and error-prone composition processes. In this paper we propose an approach to automatically discover and compose transformations: developers provide the system with the source models and specify the target metamodel. By relying on a repository of model transformations, all the possible transformation chains are calculated. Importantly, in case of incompatible intermediate target and source metamodels, proper adapters are automatically generated in order to chain also transformations that otherwise would be discarded by limiting the reuse possibilities of available transformations.

Mining metrics for understanding metamodel characteristics

Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino and Alfonso Pierantonio
MiSE, 2014
Abstract. 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.