Partial execution of Mashup Plans during modeling time

Abstract

Workflows and workflow technologies are an approved means to orchestrate services while supporting parallelism, error handling, and asynchronous messaging. A special case workflow technology is applied to are Data Mashups. In Data Mashups, workflows orchestrate services that specialize on data processing. The workflow model itself specifies the order data is processed in. Due to the fact that Data Mashups aim for usability of domain-experts with limited IT and programming knowledge, they oftentimes offer a layer on top that abstracts from the concrete workflow model and technology. This model is then transformed into an executable workflow model. However, transforming and executing the model as a whole leads to efficiency issues. In this paper, we introduce an approach to execute part of this model during modeling time. More precisely, once a specific part is modeled, it is transformed into an executable workflow fragment and executed in the backend. Consequently, once the user created the whole model, the execution time seems to be much shorter for the user because most of the model has already been processed. Furthermore, through our approach, access to intermediate results is enabled at modeling time already.