Combining Formal Verification Environments And Model Driven Engineering
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Combining Formal Verification Environments and Model-driven Engineering
Formal methods (such as interactive provers) are increasingly used in the verification of critical software. This is so because they rely on their strong formal basis and precise semantics. However, they use complex notations that are often difficult to understand. On the contrary, the tools and formalisms provided by Model Driven Engineering offer more attractive syntaxes and use intuitive notations. However, they suffer from a lack of formal foundations. In this thesis, we are interested in combining these two complementary domains that are formal methods and Model Driven Engineering. We propose an approach allowing to translate functional data types (used in interactive provers) into class diagrams and vice versa. To achieve this goal, we use a model-driven transformation method.
Formal Methods for Model-Driven Engineering
This book presents 11 tutorial lectures by leading researchers given at the 12th edition of the International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2012, held in Bertinoro, Italy, in June 2012. SFM 2012 was devoted to model-driven engineering and covered several topics including modeling languages; model transformations, functional and performance modeling and analysis; and model evolution management.
Model Driven Engineering Languages and Systems
This book constitutes the refereed proceedings of the 15th International Conference on Model Driven Engineering Languages and Systems, MODELS 2012, held in Innsbruck, Austria, in September/October 2012. The 50 papers presented in this volume were carefully reviewed and selected from a total of 181 submissions. They are organized in topical sections named: metamodels and domain specific modeling; models at runtime; model management; modeling methods and tools, consistency analysis, software product lines; foundations of modeling; static analysis techniques; model testing and simulation; model transformation; model matching, tracing and synchronization; modeling practices and experience; and model analysis.