Computer Automated Multi-Paradigm Modelling (CAMPaM)

CAMPaM acknowledges that modelling and simulation are becoming increasingly important enablers for the analysis and design of complex systems. To tackle problems of ever growing complexity, the focus of modelling and simulation research is shifting from simulation techniques to modelling methodology and technology. Because of the heterogeneous nature of for example embedded systems and the many implementation technologies, multi-paradigm modelling is a critical enabler for holistic design approaches (such as mechatronics) to avoid overdesign and to support system integration. Multi-paradigm techniques have been successfully applied in the field of software architectures, control system design, model integrated computing, and tool interoperability. Four CAMPaM workshops at Bellairs, many conference sessions, and MoDELS '06 and '07 workshops have been held. See the CAMPaM page for links to these events as well as to some (to-be-updated) related material.
CAMPaM spans the study of physical as well as software systems and combinations thereof. It adresses and integrates two orthogonal research dimensions:

1. model abstraction, concerned with the relationship between models at different levels of abstraction;
   
   
2. multi-formalism modelling, concerned with the coupling of and transformation between models described in different formalisms;
   
   

To support the above, the following enabling theories/methods/technologies are considered crucial:

1. meta-modelling, concerned with the description (models of models) of classes of models. More explictly, the specification of formalisms. Taking meta-modelling one step further, the structure, look, and behaviour of complete formalism-specific modelling environments is specified and the environments are automatically synthesized.
   
   
2. the explicit modelling of transformations, treating transformations as first-class models. This leads quite naturally to questions about (meta-)model evolution, higher-order transformations (transforming transformations), co-evolution of models, multi-view modelling and syntactic and semantic model consistency.

CAMPaM explores the possible combinations of the above notions. It combines, transforms and relates formalisms, generates maximally constrained domain- and problem-specific formalisms, methods, and (visual)tools, and verifies consistency between multiple views. Since models determined by a meta-model can always be described as graphs, transformation may be performed by a generic graph-transformation. Therefore, it makes sense to combine meta-modelling and graph transformation in a unifying framework.

1. The diversity in the research subjects of the attendees provides a fertile ground for cross-correlating research. The result of this will be the application of methods and techniques that are well-known and established in different fields of research (such as meta-modelling, graph transformation, domain-specific modelling, visual modelling environments and component-based modelling) and will lead to cross-disciplinary collaboration. Furthermore, it should make evident the need for advances of research along avenues otherwise overlooked.
   
   
2. A concerted effort of the attendees will result in a consolidation of scattered CAMPaM-related work as well as a common vision on how to best evolve the field of CAMPaM. This vision will include detailed technical perspectives, joint publications, as well as organizational plans.
   
   

We plan to focus on (some of) the following subjects during the workshop:

1. Foundations of CAMPaM/DSM:
   Meta-modelling and model transformation as enablers for multi-formalism and multi-abstraction modelling. The critical subjects (for the succesful large-scale adoption of CAMPaM) are (meta-)model evolution, (automated) model/transformation testing, model exchange, model debugging, multi-view modelling, and model consistency.
2. Foundations of multi-formalism modelling and simulation. In particular, transformation and execution frameworks for models comprised of multiple models of computation.
3. Complex Applications and how they on the one hand elicit new CAMPaM challenges driving new research and on the other hand apply and test/validate current CAMPaM state-of-the-art theory, techniques and tools.