UgameFeature: Automatic Code Generation for Unity Game Projects

Computer games are complex software systems, which means that their development requires some level of programming skills. However, their design also involves the creation of game objects (characters, scenarios, etc.), animations and story lines, which are designed by game domain experts, who in general have minimal (or no) programming skills. Game engines have been developed to facilitate game development by reducing programming efforts and enhancing productivity, but we observed that most of these engines still require programming skills in order to be used. In this paper, we discuss how Model-Driven Engineering technologies, particularly metamodelling and model transformations, can be used to facilitate game development. We define a Domain Specific Language called UGameFeature to be used by game designers to define games that can be automatically transformed into scripts that can be executed by the Unity game engine. In order to facilitate the code generation step, we defined an intermediate metamodel, so that structural differences between the UGameFeature metamodel and the Unity engine scripts can be accommodated by an intermediate model-to-model transformation. We claim that with this approach we could define a streamlined process to go from game design to game implementation, in this way surpassing the benefits already offered by game engines. We also discuss some practical obstacles of applying MDE techniques and give recommendations to practitioners who want to apply them in their projects

A FAIR Model Catalog for Ontology-Driven Conceptual Modeling Research

Conceptual models are artifacts representing conceptualizations of particular domains. Hence, multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language’s constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. However, to support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis by machines, these catalogs must be built following generally accepted quality requirements for scientific data management. Especially, all scientific (meta)data—including models—should be created using the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. In this initial release, the catalog includes over a hundred models, developed in a variety of contexts and domains. The paper also discusses the research implications for (ontology-driven) conceptual modeling of such a resource