State Propagation in Abstracted Business Processes

  • Sergey Smirnov
  • Armin Zamani Farahani
  • Mathias Weske
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7084)

Abstract

Business process models are abstractions of concrete operational procedures that occur in the daily business of organizations. Typically one model is insufficient to describe one business process. For instance, a detailed technical model may enable automated process execution, while a more abstract model supports decision making and process monitoring by business users. Thereafter, multiple models capturing one process at various levels of abstraction often coexist. While the relations between such models are studied, little is known about the relations between process instances and abstract models.

In this paper we show how the state of an abstract activity can be calculated from the states of related, detailed process activities as they happen. The approach uses activity state propagation. With state uniqueness and state transition correctness we introduce formal properties that improve the understanding of state propagation. Algorithms to check these properties are devised. Finally, we use behavioral profiles to identify and classify behavioral inconsistencies in abstract process models that might occur, once activity state propagation is used.

Keywords

Business Process Abstract Model Process Instance Activity Instance Prepare Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sergey Smirnov
    • 1
  • Armin Zamani Farahani
    • 1
  • Mathias Weske
    • 1
  1. 1.Hasso Plattner InstitutePotsdamGermany

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