Partial Repairs That Tolerate Inconsistency

  • Hendrik Decker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6909)


The consistency of databases can be supported by enforcing integrity constraints on the stored data. Constraints that are violated should be repaired by eliminating the causes of the violations. Traditionally, repairs are conceived to be total. However, it may be unfeasible to eliminate all violations. We show that it is possible to get by with partial repairs that tolerate extant inconsistencies. They may not eliminate all causes of integrity violations but preserve the consistent parts of the database. Remaining violations can be controlled by measuring inconsistency, and further reduced by inconsistency-tolerant integrity checking.


Logic Programming Integrity Constraint Deductive Database Integrity Check Minimal Repair 
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.
    Afrati, F., Kolaitis, P.: Repair checking in inconsistent databases: algorithms and complexity. In: 12th ICDT, pp. 31–41. ACM Press, New York (2009)CrossRefGoogle Scholar
  2. 2.
    Arenas, M., Bertossi, L., Chomicki, J.: Consistent query answers in inconsistent databases. In: PODS 1999, pp. 68–79. ACM Press, New York (1999)Google Scholar
  3. 3.
    Caroprese, L., Greco, S., Zumpano, E.: Active Integrity Constraints for Database Consistency Maintenance. IEEE TKDE 21(7), 1042–1057 (2009)Google Scholar
  4. 4.
    Caroprese, L., Truszczynski, M.: Active Integrity Constraints and Revision Programming. To appear in TPLP (2010),
  5. 5.
    Ceri, S., Cochrane, R., Widom, J.: Practical Applications of Triggers and Constraints: Success and Lingering Issues (10-Year Award). In: Proc. 26th VLDB, pp. 254–262. Morgan Kaufmann, San Francisco (2000)Google Scholar
  6. 6.
    Chomicki, J.: Consistent query answering: Five easy pieces. In: Schwentick, T., Suciu, D. (eds.) ICDT 2007. LNCS, vol. 4353, pp. 1–17. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Christiansen, H., Martinenghi, D.: On simplification of database integrity constraints. Fundamenta Informaticae 71(4), 371–417 (2006)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Decker, H.: Drawing Updates From Derivations. In: Kanellakis, P.C., Abiteboul, S. (eds.) ICDT 1990. LNCS, vol. 470, pp. 437–451. Springer, Heidelberg (1990)CrossRefGoogle Scholar
  9. 9.
    Decker, H.: Toward a Uniform Cause-based Approach to Inconsistency-tolerant Database Semantics. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010. LNCS, vol. 6427, pp. 983–998. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Decker, H., Martinenghi, D.: Modeling, Measuring and Monitoring the Quality of Information. In: Heuser, C.A., Pernul, G. (eds.) ER 2009. LNCS, vol. 5833, pp. 212–221. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  11. 11.
    Decker, H., Martinenghi, D.: Inconsistency-tolerant Integrity Checking. IEEE TKDE 23(2), 218–234 (2011)Google Scholar
  12. 12.
    Dung, P.M., Kowalski, R., Toni, F.: Dialectic proof procedures for assumption-based admissible argumentation. Artificial Intelligence 170(2), 114–159 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Eiter, T., Fink, M., Greco, G., Lembo, D.: Repair localization for query answering from inconsistent databases. ACM TODS 33(2) (2008)Google Scholar
  14. 14.
    Furfaro, F., Greco, S., Molinaro, C.: A three-valued semantics for querying and repairing inconsistent databases. Ann. Math. Artif. Intell. 51(2-4), 167–193 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Greco, G., Greco, S., Zumpano, E.: A logical framework for querying and repairing inconsistent databases. IEEE TKDE 15(6), 1389–1408 (2003)Google Scholar
  16. 16.
    Guessoum, A., Lloyd, J.: Updating knowledge bases. New Generation Computing 8(1), 71–89 (1990)CrossRefzbMATHGoogle Scholar
  17. 17.
    Guessoum, A., Lloyd, J.: Updating knowledge bases II. New Generation Computing 10(1), 73–100 (1991)CrossRefzbMATHGoogle Scholar
  18. 18.
    Gupta, A., Sagiv, Y., Ullman, J., Widom, J.: Constraint checking with partial information. In: Proc. PODS 1994, pp. 45–55. ACM Press, New York (1994)Google Scholar
  19. 19.
    Kakas, A., Mancarella, P.: Database updates through abduction. In: Proc. 16th VLDB, pp. 650–661. Morgan Kaufmann, San Francisco (1990)Google Scholar
  20. 20.
    Kakas, A., Kowalski, R., Toni, F.: The role of Abduction in Logic Programming. In: Handbook in Artificial Intelligence and Logic Programming, pp. 235–324 (1998)Google Scholar
  21. 21.
    Lee, S.Y., Ling, T.W.: Further improvements on integrity constraint checking for stratifiable deductive databases. In: Proc. VLDB 1996, pp. 495–505. Morgan Kaufmann, San Francisco (1996)Google Scholar
  22. 22.
    Lloyd, J., Sonenberg, L., Topor, R.: Integrity constraint checking in stratified databases. J. Logic Programming 4(4), 331–343 (1987)MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Nicolas, J.M.: Logic for improving integrity checking in relational data bases. Acta Informatica 18, 227–253 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  24. 24.
    Ramakrishnan, R., Gehrke, J.: Database Management Systems. McGraw-Hill, New York (2003)zbMATHGoogle Scholar
  25. 25.
    Sadri, F., Kowalski, R.: A theorem-proving approach to database integrity. In: Foundations of Deductive Databases and Logic Programming, pp. 313–362. Morgan Kaufmann, San Francisco (1988)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hendrik Decker
    • 1
  1. 1.Instituto Tecnológico de InformáticaValenciaSpain

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