Specifying Semantics of Evolution in Object-Oriented Databases Using Partial Deduction

  • Hele-Mai Haav
Conference paper
Part of the Workshops in Computing book series (WORKSHOPS COMP.)


In this paper, we propose a methodology for specification of semantics of evolution in object-oriented databases. Our methodology is based on Horn logic as metalanguage for specification of semantics of both schema and object evolution in object-oriented databases. Partial Deduction is used as technique for specialization of a set of general constraints on database and its schema and to derive conditions that must be satisfied to guarantee the validity of managing evolution in object-oriented databases. Implementation principles of the methodology are discussed on the basis of the object-oriented language NUT. Different types of transformations are defined that allow derivation of predicates from the descriptions of classes and objects used in the NUT system.


Partial Evaluation Integrity Constraint Class Description Database Schema Predicate Symbol 
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  1. 1.
    Sciore E. Using Annotations to Support Multiple Kinds of Versioning in an Object-Oriented Database System. ACM Transactions on Database Systems, 1991, 16: 417–438CrossRefGoogle Scholar
  2. 2.
    Ariav G. Temporally oriented data definitions: Managing schema evolution in temporally oriented databases. Data & Knowledge Engineering 1991, 6: 451–467CrossRefGoogle Scholar
  3. 3.
    Jungclaus R, Saake G, Hartmann T, Semadas C. Object-Oriented Specification of Information Systems: the TROLL Language, Braunschweig, 1991Google Scholar
  4. 4.
    Saake G, Jungclaus R. Specification of Database Applications in the TROLL Language, In: Proceedings of Int Workshop on the Specification of Database Systems, Glasgow, 1991, Springer-Verlag, London, 1991Google Scholar
  5. 5.
    Abiteboul S. Towards a deductive object-oriented database language. Data & Knowledge Engineering 1990, 5: 263–287CrossRefGoogle Scholar
  6. 6.
    van de Riet R. P. Mokum: An object-oriented active knowledge base system, Data & Knowledge Engineering 1989, 4: 21–42CrossRefGoogle Scholar
  7. 7.
    Potter W. D, Trueblood R. P and Eastman C. M. Hyper-semantic data modeling, Data & Knowledge Engineering 1989, 4: 69–90CrossRefGoogle Scholar
  8. 8.
    Tanca L. (Re-)action in Deductive Databases, In: Proceedings of Second hit. Workshop On Intelligent and Cooperative Information Systems: Core Technology For Next Generation Information Systems, Italy, October 28–30, 1991, pp 55–61Google Scholar
  9. 9.
    Lohman G. M, Lindsay B, Pirahesh H, and Schiefer K. B. Extentions to Starburst: Objects, Types, Functions, and Rules. Communications of ACM 1991, 34: 94–110CrossRefGoogle Scholar
  10. 10.
    Nguyen G. T, Rieu D. Schema evolution in object-oriented database systems. Data & Knowledge Engineering 1989, 4: 43–67CrossRefGoogle Scholar
  11. 11.
    Casais E. An Incremental Class Reorganization Approach, In: Madsen L.(ed) Proceedings of the ECOOP’92 European Conference on Object-Oriented Programming, The Netherlands, Springer-Verlag, 1992, pp 114–131CrossRefGoogle Scholar
  12. 12.
    Caruso M. and Sciore E. Meta-Functions and Contexts in an Object-Oriented Database Language. In: Proceedings of the ACM-SIGMOD Conference, Chicago III, June 1988, pp 56–68Google Scholar
  13. 13.
    Banerjee J, Kim W, et al., Semantics and Implementation of Schema Evolution in Object-Oriented Databases, In: SIGMOD Record, 1987, 16(3), pp 311–322Google Scholar
  14. 14.
    Lamb C, Landis G, Orenstein J, and Weinreb D. The Object Store Database System. Communications of ACM 1991, 34: 50–64CrossRefGoogle Scholar
  15. 15.
    Deux O, et al., The 02 System. Communications of ACM 1991, 34: 34–50CrossRefGoogle Scholar
  16. 16.
    Butterworth P, Otis A, and Stein J. The Gem Stone Object Database Management System. Communications of ACM 1991, 34: 64–78CrossRefGoogle Scholar
  17. 17.
    Komorowski J. A Specification of an Abstract Prolog Machine and Its Application to Partial Evaluation. PhD thesis, Linköping University, Sweden, 1981Google Scholar
  18. 18.
    Tyugu E, Matskin M, Penjam J, Eomois P. NUT-An object-oriented language, Computers and Artificial Intelligence 1986, 6: 521–542Google Scholar
  19. 19.
    Lloyd J. W and Shepherdson J. C. Partial evaluation in logic programming. Technical Report CS-87–09, Department of Computer Science, University of Bristol, England, 1987Google Scholar
  20. 20.
    Komorowski J. Elements of a Programming Methodology Founded on Partial Deduction-Part 1, In: Proceedings of the Fifth International Symposium on Methodologies for Intelligent Systems, Tennessee, 1990, North-Holland, pp 514–521Google Scholar
  21. 21.
    Haav H-M. An Object-oriented approach to conceptual data modelling. In: Information Modelling and Knowledge Bases III: Foundations, Theory and Applications, IOS Press, Amsterdam, 1992 pp 333–347Google Scholar
  22. 22.
    Haav H-M, Matskin M. Using Partial Deduction for automatic propagation of changes in OODB. In: Information Modelling and Knowledge Bases IV: Foundations, Theory and Applications, IOS Press, Amsterdam, 1993 (in print)Google Scholar
  23. 23.
    Eomois P. Knowledge Representation and Deduction in Extended PRIZ. In: Plander J. (ed) Artificial Intelligence and Information Control Systems of Robots, Elsevier Science Publishers B. V., North-Holland, 1984, pp 123–127Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Hele-Mai Haav
    • 1
  1. 1.Software Department, Institute of CyberneticsEstonian Academy of SciencesTallinnEstonia

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