Automated validation of conceptual schema constraints

  • T. A. Halpin
  • J. I. McCormack
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 593)


For a database application, conceptual design methods such as fact-oriented modelling and entity-relationship modelling are commonly used to specify a conceptual schema, which may then be mapped to a structure in a chosen data model (e.g. a relational database schema). Since conceptual data models support a rich variety of constraints, and these constraints may impact on one another, the task of ensuring mat the constraints expressed in a conceptual schema are consistent is non-trivial. Moreover, because different constraint patterns may be equivalent, some optimization may be needed to select the best constraint pattern for explicit assertion. With reference to conceptual schemas expressed in FOrML (an enhanced version of NIAM) mis paper discusses metarules for strong satisfiability and constraint preference, and outlines an efficient algorithm for validating four main types of constraints. Complexity analyses and benchmarks of the implemented algorithm are included.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bry, F. & Manthey, R. 1986, ‘Checking Consistency of Database Constraints: a Logical Basic', Proc. Twelfth Int. Conf. on Very Large Data Bases, VLDB, Kyoto, pp. 13–20.Google Scholar
  2. De Troyer, O., Meersman, R. & Verlinden, P. 1988, ‘RIDL* on the CRIS Case: a Workbench for NIAM', Computerized Assistance during the Information Systems Life Cycle: Proc. CRIS88, eds T.W. Olle, A.A. Verrijn-Stuart & L. Bhabuta, North-Holland, Amsterdam.Google Scholar
  3. De Troyer, O. 1989, ‘RIDL*: A Tool for the Computer-Assisted Engineering of Large Databases in the Presence of Integrity Constraints', Proc. ACM-SIGMOD Int. Conf. on Management of Data, Oregon.Google Scholar
  4. De Troyer, O. 1991, ‘The OO-Binary Relationship Model: a truly object-oriented conceptual model', Advanced Information Systems Engineering: Proc. CAiSE-91, Springer-Verlag Lecture Notes in Computer Science, no. 498, Trondheim.Google Scholar
  5. Halpin, T.A. 1989, ‘A Logical Analysis of Information Systems: static aspects of the data-oriented perspective', PhD thesis, University of Queensland.Google Scholar
  6. Halpin, T.A. 1991a, ‘Optimizing Global Conceptual Schemas', Databases in the 1990s: 2, eds B. Srinivasan & J. Zeleznikov, World Scientific, Singapore.Google Scholar
  7. Halpin, T.A. 1991b, ‘WISE: a Workbench for Information Systems Engineering', Proc. 2nd Workshop on Next Generation of CASE Tools, Trondheim.Google Scholar
  8. Halpin, T.A. 1991c, ‘A Fact-Oriented Approach to Schema Transformation', Proc. MFDBS-91, Springer-Verlag Lec. Notes in Computer Science, no. 495, Rostock.Google Scholar
  9. Halpin, T.A. 1992, ‘Fact-oriented schema optimization', to appear in Proc. CISMOD-92, India, July 1992.Google Scholar
  10. Halpin, T.A. & Orlowska, M. E. 1992, ‘Fact-Oriented Modelling for Data Analysis', Journal of Information Systems, vol. 2, no. 2, Blackwell Scientific, Oxford.Google Scholar
  11. Halpin, T.A. & Ritson, P.R. 1992, ‘Fact-Oriented Modelling and Null Values', Research and Practical Issues in Databases: Proc. 3rd Australian Database Conf., eds B. Srinivasan & J. Zeleznikov, World Scientific, Singapore.Google Scholar
  12. Lundberg, B. 1983, ‘On Correctness of Information Models', Information Systems, vol. 8, no. 2, pp. 87–93, Pergamon Press.Google Scholar
  13. Meyer, J., Weigand, H. & Wieringa, R. 1988, ‘Specifying Dynamic and Deontic Integrity Constraints', Rapport IR-175, Vrije Universiteit, Amsterdam.Google Scholar
  14. Nijssen, G.M. & Halpin, T.A. 1989, Conceptual Schema and Relational Database Design: a fact-oriented approach, Prentice Hall, Sydney.Google Scholar
  15. Qian, X. & Wiederhold, G. 1986, ‘Knowledge-based Integrity Constraint Validation', Proc. Twelfth Int. Conf. on Very Large Data Bases, Kyoto, pp. 3–12.Google Scholar
  16. Rajagopalan, P. & Ling, T.W. 1987, ‘A method for semantic validation of a class of integrity constraints', Tech. Report, Uni. of Singapore.Google Scholar
  17. Zhang, Y. & Orlowska, M.E. 1991, 'synthesizer+: an automatic tool for relational database design', Proc. 14th Australian Computer Science Conf., Sydney.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • T. A. Halpin
    • 1
  • J. I. McCormack
    • 1
  1. 1.Key Centre for Software Technology Department of Computer ScienceUniversity of QueenslandAustralia

Personalised recommendations