An Experimental CLP Platform for Integrity Constraints and Abduction

  • Slim Abdennadher
  • Henning Christiansen
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 7)


Integrity constraint and abduction are important in query-answering systems for enhanced query processing and for expressing knowledge in databases. A straightforward characterization of the two is given in a subset of the language CHRv, originally intended for writing constraint solvers to be applied for CLP languages. This subset has a strikingly simple computational model that can be executed using existing, Prolog-based technology. Together with earlier results, this confirms CHRv as a multiparadigm platform for experimenting with combinations of top-down and bottom-up evaluation, disjunctive databases and, as shown here, integrity constraint and abduction


Integrity Constraint Constraint Logic Programming Extensional Fact Declarative Semantic Constraint Logic Program 
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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  1. 1.
    Constraint handling rules online.“webchr/Google Scholar
  2. 2.
    S. Abdennadher. Operational semantics and confluence of constraint propagation rules. In Third International Conference on Principles and Practice of Constraint Programming, CP97, LNCS 1330. Springer-Verlag, November 1997.Google Scholar
  3. 3.
    S. Abdennadher and H. Schütz. CHRv: A flexible query language. Flexible Query Answering Systems, LNAI 1495, 1998.Google Scholar
  4. 4.
    H. Christiansen. Automated reasoning with a constraint-based metainterpreter. Journal of Logic Programming,37(1–3):213–254, 1998. Special issue on Constraint Logic Programming.Google Scholar
  5. 5.
    H. Christiansen. Integrity constraints and constraint logic programming. In INAP Organnizing Committee, editor, Proceedings of 12th International Conference on Applications of Prolog (INAP’99), pages 5–12, Tokyo, Japan, 1999.Google Scholar
  6. 6.
    H. Christiansen and D. Martinenghi. Symbolic constraints for meta-logic programming. Journal of Applied Artificial Intelligence,pages 345–368, 2000. Special Issue on Constraint Handling Rules.Google Scholar
  7. 7.
    H. Decker. An extension of sld by abduction and integrity maintenance for view updating in deductive databases. In Proc. of JICSLP’96, pages 157–169, 1996.Google Scholar
  8. 8.
    T. Frühwirth. Theory and practice of constraint handling rules, special issue on constraint logic programming. Journal of Logic Programming, 1998.Google Scholar
  9. 9.
    C. Holzbaur and T Frühwirth. A prolog constraint handling rules compiler and runtime system. Journal of Applied Artificial Intelligence,pages 369–388, 2000. Special Issue on Constraint Handling Rules.Google Scholar
  10. 10.
    J. Jaffar and M.J.Maher. Constraint logic programming: A survey. Journal of logic programming, 19, 20: 503–581, 1994.CrossRefGoogle Scholar
  11. 11.
    A. C. Kakas and R Mancarella. Database updates through abduction. In Proc. 16th Intl Cont. on Very Large Databases, pages 650–661. Morgan Kaufmann, California, 1990.Google Scholar
  12. 12.
    A. C. Kakas and A. Michael. Integrating abductive and constraint logic programming. In Leon Sterling, editor, Proceedings of the 12th International Conference on Logic Programming,pages 399–416, Cambridge, June 13–18 1995. MIT Press.Google Scholar
  13. 13.
    R. Kowalski, F. Toni, and G. Wetzel. Executing suspended logic programs. Fundamenta Informaticae, 34 (3): 203–224, 1998.MathSciNetMATHGoogle Scholar
  14. 14.
    G.M. Kuper, L. Libkin, and J. Paredaens, editors. Constraint Databases. Springer Verlag, 2000.Google Scholar
  15. 15.
    J. Lobo, J. Minker, and A. Rajasekar. Foundations of Disjunctive Logic Programming. MIT Press, 1992.Google Scholar
  16. 16.
    L. M. Pereira and J. J. Alferes. Well founded semantics for logic programs with explicit negation. In Bernd Neumann, editor, Proceedings of the 10th European Conference on Artificial Intelligence, pages 102–106, Vienna, Austria, August 1992. John Wiley & Sons.Google Scholar
  17. 17.
    G. Wetzel and F. Toni. Semantic query optimization through abduction and constraint handling. Flexible Query Answering Systems, LNAI 1495: 366–381, 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Slim Abdennadher
    • 1
  • Henning Christiansen
    • 2
  1. 1.Computer Science DepartmentUniversity of MunichMünchenGermany
  2. 2.Department of Computer ScienceRoskilde UniversityRoskildeDenmark

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