Deriving process specifications from augmented data models

This paper presents an approach which enables a system analyst to derive process models from data models. To accomplish this, existing data models are augmented with additional informa-tion regarding the intended process goal and the dependencies which have to be fulfilled. After giving an introductory example and pro-posing a notation for the augmentations, a sim-ple algorithm is sketched. This derives a proc-ess model consisting of all steps necessary to fulfil the specified goal and the related depend-encies.