Consistency Enforcement in Databases

  • Sebastian Link
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2582)


Consistency enforcement aims at systematically modifying a database program such that the result is consistent with respect to a specified set of integrity constraints. This modification may be done at compile-time or at run-time. The commonly known run-time approach uses rule triggering systems (RTSs). It has been shown that these systems cannot solve the problem in general.

As an alternative greatest consistent specializations (GCSs) have been studied. This approach requires the modified program specification to be a maximal consistent diminution of the original one with respect to some partial order. The chosen order is operational specialization. On this basis it is possible to derive a commutativity result and a compositionality result. The first one enables step-by-step enforcement for sets of constraints. The second one reduces the problem to providing the GCSs just for basic operations, whereas for complex programs the GCS can be easily determined. The approach turns out to be well-founded since the GCS for such complex programs is effectively computable if we require loops to be bounded.

Despite its theoretical merits the GCS approach is still too coarse. This leads to the problem of modifying the chosen specialization order and to relax the requirement that the result should be unique. One idea is to exploit the fact that operational specialization is equivalent to the preservation of a set of transition invariants. In this case a reasonable order arises from a slight modification of this set, in which case we talk of a maximal consistent effect preserver (MCE). However, a strict theory of MCEs is still outstanding.


Static Constraint Integrity Constraint Proof Obligation Predicate Transformer Program Semantic 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    J. Bell, M. Machover. A Course in Mathematical Logic. North-Holland 1977.Google Scholar
  2. 2.
    S. Ceri, P. Fraternali, S. Paraboschi, L. Tanca: Automatic Generation of Production Rules for Integrity Maintenance. ACM TODS 19(3), 1994, 367–422.CrossRefGoogle Scholar
  3. 3.
    I. A. Chen, R. Hull, D. McLeod. An Execution Model for Limited Ambiguity Rules and its Applications to Derived Data Update. ACM ToDS 20, 1995, 365–413.CrossRefGoogle Scholar
  4. 4.
    L. Console, M. L. Sapino, D. Theseider. The Role of Abduction in Database View Updating. Journal of Intelligent Information Systems 4, 1995, 261–280.CrossRefGoogle Scholar
  5. 5.
    H. Decker. One Abductive Logic Programming Procedure for two Kinds of Update. Proc. DYNAMICS’97, 1997.Google Scholar
  6. 6.
    M. Dekhtyar, A. Dikovsky, S. Dudakov, N. Spyratos. Maximal Expansions of Database Updates. In K.-D. Schewe, B. Thalheim (Eds.). Foundations of Information and Knowledge Systems, 72–87. Springer LNCS 1762, 2000.CrossRefGoogle Scholar
  7. 7.
    M. Gertz. Specifying Reactive Integrity Control for Active Databases. Proc. RIDE’ 94, 1994, 62–70.Google Scholar
  8. 8.
    S. Link. Eine Theorie der Konsistenzerzwingung auf der Basis arithmetischer Logik. M.Sc. Thesis (in German). TU Clausthal 2000.Google Scholar
  9. 9.
    S. Link, K.-D. Schewe. An Arithmetic Theory of Consistency Enforcement. Acta Cybernetica. vol. 15. 2002. 379–416.zbMATHMathSciNetGoogle Scholar
  10. 10.
    J. Lobo, G. Trajcevski. Minimal and Consistent Evolution in Knowledge Bases. Journal of Applied Non-Classical Logics 7, 1997, 117–146.zbMATHMathSciNetGoogle Scholar
  11. 11.
    M. Makkai. Admissible Sets and Infinitary Logic. In J. Barwise (Ed). Handbook of Mathematical Logic. North Holland, Studies in Logic and Foundations of Mathematics. vol. 90: 233–281. 1977.Google Scholar
  12. 12.
    E. Mayol, E. Teniente. Dealing with Modification Requests During View Updating and Integrity Constraint Maintenance. In K.-D. Schewe, B. Thalheim (Eds.). Foundations of Information and Knowledge Systems, 192–212. Springer LNCS 1762, 2000.CrossRefGoogle Scholar
  13. 13.
    G. Nelson. A Generalization of Dijkstra’s Calculus. ACM TOPLAS. vol. 11 (4): 517–561. 1989.CrossRefGoogle Scholar
  14. 14.
    K.-D. Schewe. Consistency Enforcement in Entity-Relationship and Object-Oriented Models. Data and Knowledge Engineering 28, 1998, 121–140.zbMATHCrossRefGoogle Scholar
  15. 15.
    K.-D. Schewe. Fundamentals of Consistency Enforcement. In H. Jaakkola, H. Kangassalo, E. Kawaguchi (eds.). Information Modelling and Knowledge Bases X: 275–291. IOS Press 1999.Google Scholar
  16. 16.
    K.-D. Schewe, B. Thalheim. Towards a Theory of Consistency Enforcement. Acta Informatica. vol. 36: 97–141. 1999.zbMATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    K.-D. Schewe, B. Thalheim. Limitations of Rule Triggering Systems for Integrity Maintenance in the Context of Transition Specifications. Acta Cybernetica. vol. 13: 277–304. 1998.zbMATHMathSciNetGoogle Scholar
  18. 18.
    K.-D. Schewe, B. Thalheim, J. Schmidt, I. Wetzel. Integrity Enforcement in Object Oriented Databases. In U. Lipeck, B. Thalheim (eds.). Modelling Database Dynamics: 174–195. Workshops in Computing. Springer 1993.Google Scholar
  19. 19.
    E. Teniente, A. Olivé. Updating Knowledge Bases while Maintaining their Consistency. The VLDB Journal 4, 1995, 193–241.CrossRefGoogle Scholar
  20. 20.
    B. Wüthrich. On Updates and Inconsistency Repairing in Knowledge Bases. Proc. ICDE’93, 1993, 608–615.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Sebastian Link
    • 1
  1. 1.Information Science Research CentreMassey University, Information SystemsPalmerston NorthNew Zealand

Personalised recommendations