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Automated Error Correction of Business Process Models

  • Mauro Gambini
  • Marcello La Rosa
  • Sara Migliorini
  • Arthur H. M. Ter Hofstede
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6896)

Abstract

As order dependencies between process tasks can get complex, it is easy to make mistakes in process model design, especially behavioral ones such as deadlocks. Notions such as soundness formalize behavioral errors and tools exist that can identify such errors. However these tools do not provide assistance with the correction of the process models. Error correction can be very challenging as the intentions of the process modeler are not known and there may be many ways in which an error can be corrected. We present a novel technique for automatic error correction in process models based on simulated annealing. Via this technique a number of process model alternatives are identified that resolve one or more errors in the original model. The technique is implemented and validated on a sample of industrial process models. The tests show that at least one sound solution can be found for each input model within a reasonable response time.

Keywords

Business Process Management Edit Operation Structural Distance Output Place Edit Sequence 
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

  • Mauro Gambini
    • 1
  • Marcello La Rosa
    • 2
    • 3
  • Sara Migliorini
    • 1
  • Arthur H. M. Ter Hofstede
    • 2
    • 3
    • 4
  1. 1.University of VeronaItaly
  2. 2.Queensland University of TechnologyAustralia
  3. 3.NICTA Queensland LabAustralia
  4. 4.Eindhoven University of TechnologyThe Netherlands

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