Generative technologies for model animation in the TopCased platform

International audienceDomain Specific Modeling Languages (DSML) are more and more used to handle high level concepts, and thus bring complex software development under control. The increasingly recurring definition of new languages raises the problem of the definition of support tools such as editor, simulator, compiler, etc. In this paper we propose generative technologies that have been designed to ease the development of model animation tools inside the TopCased platform. These tools rely on the automatically generated graphical editors of TopCased and provide additional generators for building model animator graphical interface. We also rely on an architecture for executable metamodel (i.e., the TopCased model execution metamodeling pattern) to bind the behavioral semantics of the modeling language. These tools were designed in a pragmatic manner by abstracting the various model animators that had been hand-coded in the TopCased project, and then validated by refactoring these animators

Generative technologies for model animation in the TopCased platform

International audienceDomain Specific Modeling Languages (DSML) are more and more used to handle high level concepts, and thus bring complex software development under control. The increasingly recurring definition of new languages raises the problem of the definition of support tools such as editor, simulator, compiler, etc. In this paper we propose generative technologies that have been designed to ease the development of model animation tools inside the TopCased platform. These tools rely on the automatically generated graphical editors of TopCased and provide additional generators for building model animator graphical interface. We also rely on an architecture for executable metamodel (i.e., the TopCased model execution metamodeling pattern) to bind the behavioral semantics of the modeling language. These tools were designed in a pragmatic manner by abstracting the various model animators that had been hand-coded in the TopCased project, and then validated by refactoring these animators

Exploration sémantique des modèles socio-environnementaux: Approche générique pour l'initialisation et l'observation des modèles de simulation complexes

Researchers have sought to deal with the complexity of socio-ecosystems including biophysical and social dynamics, and their interactions. In order to cope with this complexity, they need increasingly complex models, whose initialization, and observation are becoming very difficult to implement. However, no generic framework has yet been developed to address this issue. The objective of the thesis is a generic framework for specifying and implementing the initialization from numerous heterogeneous data, and the observation producing the desired indicators. The result is a set of tools and know-how, allowing thematicians to specify and automate the whole process of exploitation of a simulation model, from the initialization to the production of indicators. For this, we propose to formulate the initialization and observation as transformations among data and data structures. This formulation allows to use the Model Driven Engineering (MDE) concepts in order to implement the generic framework and the corresponding domain specific languages (DSL) allow thematicians to specify easier initialization and observation SES models.Les chercheurs veulent aborder toute la complexité des socio-écosystèmes (SES) afférents aux dynamiques biophysiques, sociales ainsi qu’à leurs interactions. Afin d'aborder cette complexité, ils ont recours à des modèles de simulation de plus en plus complexes, dont l'initialisation et l'observation sont devenues difficiles à mettre en œuvre. Toutefois, aucun cadre générique n'a encore été développé pour résoudre ce problème. L’objectif de cette thèse est de proposer un cadre générique pour la spécification et la mise en œuvre de l'initialisation, à partir de nombreuses données hétérogènes, et l'observation pour produire les indicateurs souhaités par les thématiciens. Le résultat est un ensemble d’outils et de savoir-faire, permettant aux thématiciens de spécifier et d’automatiser l'ensemble du processus d'exploitation d’un modèle de simulation, de l'initialisation à la production des indicateurs. Pour cela, nous proposons de formuler l'initialisation et l'observation des modèles de simulation en des transformations entre données et structures de données. Cette formulation permet d'utiliser les concepts de l’ingénierie dirigée par les modèles (IDM) afin de mettre en œuvre des langages dédiés (DSL). Ces derniers fournissent les concepts nécessaires permettant aux thématiciens de spécifier plus facilement l’initialisation et l’observation de modèles de SES