Challenges Observed in the Definition of Reference Business Processes

  • Liming Zhu
  • Leon J. Osterweil
  • Mark Staples
  • Udo Kannengiesser
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4928)


In many modern enterprises, explicit business process definitions facilitate the pursuit of business goals in such ways as best practice reuse, process analysis, process efficiency improvement, and automation. Most real-world business processes are large and complex. Successfully capturing, analysing, and automating these processes requires process definition languages that capture a variety of process aspects with a wealth of details. Most current process modeling languages, such as Business Process Modeling Notation (BPMN), focus on structural control flows among activities while providing inadequate support for other process definition needs. In this paper, we first illustrate these inadequacies through our experiences with a collection of real-world reference business processes from the Australian lending industry. We observe that the most significant inadequacies include lack of resource management, exception handling, process variation, and data flow integration. These identified shortcomings led us to consider the Little-JIL language as a vehicle for defining business processes. Little-JIL addresses the afore-mentioned inadequacies with a number of innovative features. Our investigation concludes that these innovative features are effective in addressing a number of key reference business process definition needs.


Business Process Business Process Execution Language Process Definition Business Process Modelling Notation Valuation Firm 
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 2008

Authors and Affiliations

  • Liming Zhu
    • 1
    • 2
  • Leon J. Osterweil
    • 3
  • Mark Staples
    • 1
    • 2
  • Udo Kannengiesser
    • 1
    • 2
  1. 1.Empirical Software EngineeringNICTANSWAustralia
  2. 2.School of Computer Science and EngineeringUniversity of New South Wales 
  3. 3.Laboratory for Advanced Software Engineering Research (LASER)University of Massachusetts at AmherstAmherst 

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