Advertisement

Tabularizing the Business Knowledge: Automated Detection and Fixing of Anomalies

  • Nicola Boffoli
  • Daniela Castelluccia
  • Giuseppe Visaggio
Conference paper
Part of the Lecture Notes in Information Systems and Organisation book series (LNISO, volume 6)

Abstract

Formalizing the business knowledge makes it easy to understand for decision-makers aiming at improving the business processes. However, extracting, structuring and formalizing the business rules and constraints and then managing the variability of decision points could be difficult without an effective support. The authors’ research explores the benefits of the application of decision tables, finding additional advantages in detecting and fixing several anomalies that may affect the business knowledge. Decision tables are able to guarantee non-redundancy, consistency and completeness. The authors have implemented a software tool to automate decision tables in practice and describe a running example to give perception of these advantages.

Keywords

Business rules Decision tables Verification and validation 

References

  1. 1.
    Boffoli, N., Caivano, D., Castelluccia, D., Visaggio, G.: Business process lines and decision tables driving flexibility by selection. In: Gschwind, T., De Paoli, F., Gruhn, V., Book, M. (eds.) Software Composition. LNCS, vol. 7306, pp. 178–193. Springer, Berlin (2012)Google Scholar
  2. 2.
    Boffoli, N., Castelluccia, D., Visaggio, G.: Tabularizing the business knowledge: modeling, maintenance and validation. In: Spagnoletti, P. (ed.) Organizational Change and Information Systems. LNISO, vol. 2, pp. 471–479. Springer, Berlin (2013)Google Scholar
  3. 3.
    Date, C.: What Not How. The Business Rule Approach to Application Development. Addison-Wesley, Boston (2000)Google Scholar
  4. 4.
    Odell, J.: Business rules. In: Object Magazine, pp. 53–56 (1995)Google Scholar
  5. 5.
    Preece, A., Shinghal, R.: Foundation and application of knowledge base verification. Int. J. Intell. Syst. 9(8), 683–702. Wiley (1994)Google Scholar
  6. 6.
    Maes, R., Van Dijk, J.E.M.: On the role of ambiguity and incompleteness in the design of decision tables and rule-based systems. Comput. J. 31(6), 481–489. Oxford University Press (1988)Google Scholar
  7. 7.
    Vanthienen, J., Mues, C., Wets, G., Delaere, K.: A tool-supported approach to inter-tabular verification. Expert Syst. Appl. 15(3–4), 277–285. Elsevier (1998)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nicola Boffoli
    • 1
    • 2
  • Daniela Castelluccia
    • 1
    • 3
  • Giuseppe Visaggio
    • 1
    • 2
    • 3
  1. 1.Department of InformaticsUniversity of BariBariItaly
  2. 2.SER and Practices, Software Engineering Research and PracticesUniversity of BariBariItaly
  3. 3.DAISY-Net, Driving Advances of ICT in South ItalyPublic-Private Consortium Joining the Competence Centre of ICT-SudBariItaly

Personalised recommendations