This repository is part of a research project and was supported by the Ministry of Education of Spain (FPU grant FPU13/02698); the Spanish MINECO (TIN2014-52129-R); the R&D programme of the Madrid Region (S2013/ICE-3006); the Austrian agency for international mobility and cooperation in education, science and research (OeAD) by funds from the Austrian Federal Ministry of Science, Research and Economy - BMWFW (ICM-2016-04969); and by the Christian Doppler Forschungsgesellschaft, the Federal Ministry of Economy, Family and Youth and the National Foundation for Research, Technology and Development, Austria.
Contributions:
Ángel Mora Segura, Juan de Lara, Patrick Neubauer, Manuel Wimmer. Automated modelling assistance by integrating heterogeneous information sources. Computer Languages, Systems & Structures, Volume 53, 2018, p.90-120, ISSN 1477-8424, https://doi.org/10.1016/j.cl.2018.02.002. (http://www.sciencedirect.com/science/article/pii/S1477842417301690)
Abstract:
Model-Driven Engineering (MDE) uses models as its main assets in the software development process. The structure of a model is described through a meta-model. Even though modelling and meta-modelling are recurrent activities in MDE and a vast amount of MDE tools exist nowadays, they are tasks typically performed in an unassisted way. Usually, these tools cannot extract useful knowledge available in heterogeneous information sources like XML, RDF, CSV or other models and meta-models. We propose an approach to provide modelling and meta-modelling assistance. The approach gathers heterogeneous information sources in various technological spaces, and represents them uniformly in a common data model. This enables their uniform querying, by means of an extensible mechanism, which can make use of services, e.g., for synonym search and word sense analysis. The query results can then be easily incorporated into the (meta-)model being built. The approach has been realized in the Extremo tool, developed as an Eclipse plugin. Extremo has been validated in the context of two domains – production systems and process modelling – taking into account a large and complex industrial standard for classification and product description. Further validation results indicate that the integration of Extremo in various modelling environments can be achieved with low effort, and that the tool is able to handle information from most existing technological spaces.
Ángel Mora Segura, Juan de Lara, Patrick Neubauer, Manuel Wimmer,
Computer Languages, Systems & Structures, Volume 53, 2018, p.90-120, ISSN 1477-8424, https://doi.org/10.1016/j.cl.2018.02.002. (http://www.sciencedirect.com/science/article/pii/S1477842417301690)
Abstract:
Model-Driven Engineering (MDE) uses models as its main assets in the software development process. The structure of a model is described through a meta-model. Even though modelling and meta-modelling are recurrent activities in MDE and a vast amount of MDE tools exist nowadays, they are tasks typically performed in an unassisted way. Usually, these tools cannot extract useful knowledge available in heterogeneous information sources like XML, RDF, CSV or other models and meta-models. We propose an approach to provide modelling and meta-modelling assistance. The approach gathers heterogeneous information sources in various technological spaces, and represents them uniformly in a common data model. This enables their uniform querying, by means of an extensible mechanism, which can make use of services, e.g., for synonym search and word sense analysis. The query results can then be easily incorporated into the (meta-)model being built. The approach has been realized in the Extremo tool, developed as an Eclipse plugin. Extremo has been validated in the context of two domains – production systems and process modelling – taking into account a large and complex industrial standard for classification and product description. Further validation results indicate that the integration of Extremo in various modelling environments can be achieved with low effort, and that the tool is able to handle information from most existing technological spaces.
Ángel Mora Segura, Juan de Lara.
Science of Computer Programming, Volume 180, 2019, p.71-80, ISSN 0167-6423, https://doi.org/10.1016/j.scico.2019.05.003. (http://www.sciencedirect.com/science/article/pii/S0167642319300644)
Abstract:
Modelling is a core activity in software development paradigms like Model-driven Engineering (MDE). Therefore, the quality of (meta-)models is crucial for the success of software projects. However, many times, modelling becomes a purely manual activity, which does not take advantage of information embedded in heterogeneous information sources, such as XML documents, ontologies, or other models and meta-models. In order to improve this situation, we present Extremo, an Eclipse plugin aimed at gathering the information stored in heterogeneous sources in a common data model, to facilitate the reuse of information chunks in the model being built. The tool covers the steps needed to incorporate this knowledge within an external modelling tool, supporting the uniform query of the heterogeneous sources and the evaluation of constraints. Flexibility of the main features (e.g., supported data formats, queries) is achieved by means of extensible mechanisms. To illustrate the usefulness of Extremo, we describe a practical case study in the financial domain and evaluate its performance and scalability.