Industrial large scale asynchronous and synchronous collaborative modeling with fine-grained domain-independent delta models

Model-based systems engineering is the measure to master the ever-growing complexity of the industrial system. The combination of complex engineering data with process support, such as project and change management, constitutes the integrated development environment. The collaboration is challenging, as it is characterized by (1) large-scaled evolving meta-model and model, (2) long modeling time, (3) and many modelers dispersed at different locations. This thesis presents the concept and realization addressing these challenges. An approach supporting both collaborative asynchronous and synchronous modeling has been proposed. Asynchronous collaborative modeling has the advantage of the availability of historic information and has fewer time constraints. Synchronous collaborative modeling enables close interaction among modelers. The combination of these two complementary ways of collaboration enables flexible collaboration. In this work, collaboration on large scale model is supported. Delta model is the central aspect to resolve the problems of performance. Delta model represents the difference between two models. Furthermore, as the delta model is fine-grained, the storage can be kept to a minimum. The data model of the delta model is domain independent. Therefore, the approach can be applied to different meta-models. The generic nature of the delta model also ensures the maintainability and scalability to the changes in software. In this work, statistical analysis based on a practical example has been taken to verify the approach. The technical implementation here is based on the PREEvision® tool. However, the principle is generic and is portable to other approaches.