A new paradigm for the enactment and dynamic adaptation of datadriven process structures

Abstract. Industry is increasingly demanding IT support for large en-gineering processes, i.e., process structures consisting of hundreds up to thousands of processes. Developing a car, for example, requires the co-ordination of development processes for hundreds of components. Each of these development processes itself comprises a number of interdepen-dent processes for designing, testing, and releasing the respective compo-nent. Typically, the resulting process structure becomes very large and is characterized by a strong relation with the assembly of the product. Such process structures are denoted as data-driven. On the one hand, the strong linkage between data and processes can be utilized for auto-matically creating process structures. On the other hand, it is useful for (dynamically) adapting process structures at a high level of abstraction. This paper presents new techniques for (dynamically) adapting data-driven process structures. We discuss fundamental correctness criteria needed for (automatically) detecting and disallowing dynamic changes which would lead to an inconsistent runtime situation. Altogether, our COREPRO approach provides a new paradigm for changing data-driven process structures at runtime reducing costs of change significantly