Business Process Lines and Decision Tables Driving Flexibility by Selection

  • Nicola Boffoli
  • Danilo Caivano
  • Daniela Castelluccia
  • Giuseppe Visaggio
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7306)


A major challenge faced by organizations is to better capture business strategies into products and services at an ever-increasing pace as the business environment constantly evolves. We propose a novel methodology base on a Business Process Line (BPL) engineering approach to inject flexibility into process modeling phase and promote reuse and flexibility by selection. Moreover we suggest a decision-table (DT) formalism for eliciting, tracking and managing the relationships among business needs, environmental changes and process tasks. In a real case study we practiced the proposed methodology by leveraging the synergy of feature models, variability mechanisms and decision tables. The application of DT-based BPL engineering approach proves that the Business Process Line benefits from fundamental concepts like composition, reusability and adaptability and satisfies the requirements for process definition flexibility.


business process management business process modeling business process line feature model variability mechanisms decision table 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Duan, Y., Huadong, M.: Modelling flexible workflow based on temporal logic. In: The 9th International Conference on Computer Supported Cooperative Work in Design Proceedings, May 24-26, vol. 1, pp. 594–599 (2005)Google Scholar
  2. 2.
    Nurcan, S., Edme, M.H.: Intention Driven Modelling for Flexible Workflow Applications. Special issue of the Software Process: Improvement and Practice Journal on Business Process Management, Development and Support 10, 4 (2005)Google Scholar
  3. 3.
    Hammer, M., Champy, J.: Reengineering the Corporation-A manifesto for Business Revolution. Harper Business (1994)Google Scholar
  4. 4.
    Schnieders, A., Puhlmann, F.: Variability Mechanisms in E-Business Process Families. In: Abramowicz, W., Mayr, H.C. (eds.) Proceedings of the 9th International Conference on Business Information Systems, BIS 2006. Lecture Notes in Informatics, vol. 85, pp. 583–601. GI (2006)Google Scholar
  5. 5.
    Regev, G., Wegmann, A.: A Regulation Based View on Business Process and Supporting System Flexibility. In: Proceedings of the CaiSE 2005 Workshops, vol. 1, pp. 91–98 (2005)Google Scholar
  6. 6.
    Nurcan, S.: A survey on the flexibility requirements related to business processes and modeling artifacts. In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences, Big Island, Hawaii, USA (2008)Google Scholar
  7. 7.
    Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. SEI Series in Software Engineering. Addison–Wesley (August 2001)Google Scholar
  8. 8.
    Ommering, R.V.: Building product populations with software components. In: ICSE 2002, Orlando, Florida (2002)Google Scholar
  9. 9.
    Thomphson, J., Heimdalh, M.P.: Extending the Product Family Approach to support n-Dimensional and Hierarchical Product Lines. In: 5th IEEE Symposium on Requirements Engineering, Toronto, Canada (2001)Google Scholar
  10. 10.
    Svahnberg, M., Van Gurp, J., Bosch, J.: On the notion of variability in Software Product Lines. In: Working IEEE/IFIP Conference on Software Architecture (2001)Google Scholar
  11. 11.
    Pohl, K., Böckle, G., Linden, F.J.: Software Product Line Engineering: Foundations, Principles and Techniques. Springer Verlag New York, Inc. (2005)Google Scholar
  12. 12.
    Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-oriented domain analysis (FODA) feasibility study, Technical Report CMU/SEI-90-TR-021, SEI, Carnegie Mellon University (November 1990)Google Scholar
  13. 13.
    Schnieders, A., Puhlmann, F.: Variability Mechanisms in E-Business Process Families. In: Proceedings of the 9th International Conference on Business Information Systems, BIS 2006, Klagenfurt, Austria, pp. 583–601 (2006)Google Scholar
  14. 14.
    Malone, T.W., Crowston, K., Herman, G.A.: Organizing Business Knowledge The MIT Process Handbook. MIT Press, Cambridge (2003)Google Scholar
  15. 15.
    Vanthienen, J., Mues, C., Wets, G., Delaere, K.: A tool-supported approach to inter-tabular verification. Expert Systems with Applications 15, 277–285 (1998)CrossRefGoogle Scholar
  16. 16.
    Maes, R., Van Dijk, J.E.M.: On the Role of Ambiguity and Incompleteness in the Design of Decision Tables and RuleBased Systems: The Computer Journal 31(6) (1988)Google Scholar
  17. 17.
    Ho, T.B., Cheung, D., Liu, H.: Advances in Knowledge Discovery and Data Mining. In: 9th Pacific-Asia Conference, Vietnam (2005)Google Scholar
  18. 18.
    Bar-Or, A., Keren, D., Schuster, A., Wolff, R.: Hierarchical Decision Tree Induction in Distributed Genomic Databases. IEEE Transactions on Knowledge and Data Engineering 17 (2005)Google Scholar
  19. 19.
    Antoniu, G., van Harmelen, F., Plant, R., Vanthienen, J.: Verification and Validation of Knowledge-Based Systems: Report on Two 1997 Events. AI Magazine 19(3), 123–126 (1998)Google Scholar
  20. 20.
    Larsen, H., Nonfjall, H.: Modeling in the Design of a KBS Validation System. Int. Journal of Intelligent Systems 6, 759–775 (1991)CrossRefGoogle Scholar
  21. 21.
    Zhang, D., Nguyen, D.: A Tool for Knowledge Base Verification. IEEE Transactions on Knowledge and Data Engineering 6(6), 983–989 (1994)CrossRefGoogle Scholar
  22. 22.
    Zlatareva, N.: A Framework for Verification, Validation, and Refinement of Knowledge Bases: The VVR System. Int. Journal of Intelligent Systems 9, 703–737 (1994)CrossRefGoogle Scholar
  23. 23.
    Preece, A., Shinghal, R.: Foundation and Application of Knowledge Base Verification. Int. Journal of Intelligent Systems 9, 683–701 (1994)CrossRefGoogle Scholar
  24. 24.
    Chen, L., Ali Babar, M., Ali, N.: Variability management in software product lines: A systematic review. In: SPLC 2009, San Francisco, CA, USA, pp. 81–90 (2009)Google Scholar
  25. 25.
    Dadam, P., Reichert, M.: The ADEPT project: a decade of research and development for robust and flexible process support. Computer Science - R&D 23(2), 81–97 (2009)CrossRefGoogle Scholar
  26. 26.
    Aiello, M., Bulanov, P., Groefsema, H.: Requirements and Tools for Variability Management. In: 34th Annual IEEE Computer Software and Applications Conference Workshops, COMPSACW, pp. 245–250 (2010)Google Scholar
  27. 27.
    Rosa, M.L., Dumas, M., Hofstede, A., Mendling, J.: Configurable multi-perspective business process models. Information Systems 26(2) (2011)Google Scholar
  28. 28.
    Rolland, C., Nurcan, S.: Business Process Lines to Deal with the Variability. In: Proceedings of 43rd Hawaii International Conference on System Sciences, HICSS (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nicola Boffoli
    • 1
  • Danilo Caivano
    • 1
  • Daniela Castelluccia
    • 1
  • Giuseppe Visaggio
    • 1
  1. 1.Department of InformaticsUniversity of BariBariItaly

Personalised recommendations