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)

Abstract

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lending Industry XML Initiative (LIXI), http://www.lixi.org.au
  2. 2.
    van der Aalst, W.M.P., ter Hofstede, A.H.M.: YAWL: Yet Another Workflow Language. Information Systems 30(4), 245–275 (2005)CrossRefGoogle Scholar
  3. 3.
    Becker, J., Delfmann, P., Dreiling, A., Knackstedt, R., Kuropka, D.: Configurative Process Modeling - Outlining an Approach to Increased Business Process Model Usability. In: Information Resources Management Association Conference (2004)Google Scholar
  4. 4.
    Desai, N., Mallya, A.K., Chopra, A.K., Singh, M.P.: Interaction protocols as design abstractions for business processes. IEEE Transaction on Software Engineering 31(12), 1015–1027 (2005)CrossRefGoogle Scholar
  5. 5.
    Eriksson, H.-E., Penker, M.: Business modeling with UML: Business Patterns at Work. John Wiley & Sons, New York (2000)Google Scholar
  6. 6.
    Georgakopoulos, D., Hornick, M.F., Sheth, A.P.: An Overview of Workflow Management: From Process Modeling to Workflow Automation Infrastructure. Distributed and Parallel Database (3), 119–153 (1995)CrossRefGoogle Scholar
  7. 7.
    Grigori, D., Casati, F., Dayal, U., Shan, M.-C.: Improving Business Process Quality through Exception Understanding, Prediction, and Prevention. In: 27th International Conference on Very Large Data Bases (VLDB) (2001)Google Scholar
  8. 8.
    Gruhn, V., Laue, R.: What business process modelers can learn from programmers. Science of Computer Programming 65(1), 4–13 (2007)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Klein, M., Dellarocas, C.: A Knowledge-Based Approach to Handling Exceptions in Workflow Systems. Computer Supported Cooperative Work (CSCW) 9, 339–412 (2000)Google Scholar
  10. 10.
    Laguna, M., Marklund, J.: Business process modeling, simulation, and design. Pearson/Prentice Hall, Upper Saddle River, NJ (2004)Google Scholar
  11. 11.
    Muehlen, Z., Rosemann, M.M.: Multiparadigm process management. In: The Fifth Workshop on Business Process Modeling, Development, and Support (BPMDS) (2004)Google Scholar
  12. 12.
    OMG, Business Process Modeling Notation Specification (version 1.0 Final Adopted Version) (2006)Google Scholar
  13. 13.
    Osterweil, L.: Software Processes Are Software, Too, Revisited. In: 19th International Conference on Software Engineering (ICSE), Boston, MA, pp. 540–558 (1997)Google Scholar
  14. 14.
    Osterweil, L., Sondheimer, N.K., Clarke, L.A., Katsh, E., Rainey, D.: Using Process Definitions to Facilitate the Specifications of Requirements. In: Department of Computer Science, University of Massachusetts, Amherst, MA (2006)Google Scholar
  15. 15.
    Rolland, C.: A comprehensive View of Process Engineering. In: Pernici, B., Thanos, C. (eds.) CAiSE 1998. LNCS, vol. 1413, Springer, Heidelberg (1998)Google Scholar
  16. 16.
    Russell, N., van der Aalst, W.M.P., ter Hofstede, A.H.M.: Exception Handling Patterns in Process-Aware Information Systems, BPM Center Report BPM-06-04 (2006)Google Scholar
  17. 17.
    Russell, N., ter Hofstede, A.H.M., van der Aalst, W.M.P., Mulyar, N.: Workflow Control-Flow Patterns: A Revised View, BPMcenter.org BPM Center Report BPM-06-22 (2006)Google Scholar
  18. 18.
    Russell, N., ter Hofstede, A.H.M., Edmond, D., van der Aalst, W.M.P.: Workflow Data Patterns, Queensland University of Technology FIT-TR-2004-01 (2004)Google Scholar
  19. 19.
    Russell, N., ter Hofstede, A.H.M., Edmond, D., van der Aalst, W.M.P.: newYAWL: Achieving Comprehensive Patterns Support in Workflow for the Control-Flow, Data and Resource Perspectives, BPMcenter.org (2007)Google Scholar
  20. 20.
    Russell, N., ter Hofstede, A.H.M., Edmond, D., van der Aalst, W.M.P.: Workflow Resource Patterns, Eindhoven University of Technology BETA Working Paper Series, WP. 127 (2004)Google Scholar
  21. 21.
    Simidchieva, B.I., Clarke, L.A., Osterweil, L.J.: Representing Process Variation with a Process Family. In: International Conference on Software Process (ICSP) (2007)Google Scholar
  22. 22.
    Ward, P.T.: The transformation schema: An extension of the data flow diagram to represent control and timing. IEEE Transaction on Software Engineering 12(2), 198–210 (2005)Google Scholar
  23. 23.
    Wise, A.: Little-JIL 1.5 Language Report, Department of Computer Science, University of Massachusetts, Amherst, MA (2006)Google Scholar

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 

Personalised recommendations