The Object Flow Model: A formal framework for describing the dynamic construction, destruction and interaction of complex objects

  • Lissa F. Pollacia
  • Lois M. L. Delcambre
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 823)


This research complements active object-oriented database management systems by providing a formal, yet conceptually-natural model for complex object construction and destruction. The Object Flow Model (OFM), introduced in this paper, assumes an object-oriented database for the rich structural description of objects and for the specification of methods to manipulate objects. The OFM contributes a third component, the Object Flow Diagram (OFD), which provides a visual formalism to describe how multiple objects and events can actively invoke processing steps, how objects can become part of progressively more complex objects, and how complex objects can be picked apart. The OFD thus provides an invocation mechanism that is more general than a single message and a processing mechanism that may invoke multiple methods (so long as they apply to either the input or output objects). The development of the OFD was influenced by conceptual modeling languages and discrete event simulation languages and the formal semantics of the OFD is based on work in deductive databases.


Formal Semantic Complex Object Process Node Deductive Database Process Definition 
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. [Abit90]
    Abiteboul, S., Simon, E. “Fundamental Properties of Deterministic and Nondeterministic Extensions of Datalog”, Journal of Theoretical Computer Science, 1990.Google Scholar
  2. [Ban88]
    Bancilhon, F. et. al. “The Design and Implementation Of 02, an Object-Oriented Database System”, Advances in Object-oriented Database Systems, Lecture Notes in Computer Science, Vol. 334., Springer-Verlag, Berlin, 1988, 1–22.Google Scholar
  3. [Bro84]
    Brodie, M. L., Mylopoulos, J., Schmidt, J. W. (eds.) On Conceptual Modeling: Perspectives from Artificial Intelligence, Databases, and Programming Languages, Springer-Verlag, N.Y., 1984.Google Scholar
  4. [Bro84b]
    Brodie, M. L., Ridjanovic, D. “On the Design and Specification of Database Transactions”, in [Bro84], 277–306.Google Scholar
  5. [Day90]
    Dayal, U., Hsu, M., Ladin, R. “Organizing Long-Running Activities with Triggers and Transactions”, Proc. of ACM SIGMOD Conf., 1990, 204–214.Google Scholar
  6. [Del88]
    Delcambre, L., Etheredge, J. “The Relational Production Language: A Production Language for Relational Databases”, Proc. 2nd Int'l Conf. on Expert Database Systems, Tysons Corner, VA., April 1988.Google Scholar
  7. [Geh91]
    Gehani, N., Jagadish, H.V. “Ode as an Active Database: Constraints and Triggers”, Proc. 17th Int'l Conf. on VLDB, Sept. 1991.Google Scholar
  8. [Hal91]
    Hall, G., Gupta, R. “Modeling Transition”, Proc. of 1991 Data Eng. Conf., 540–549.Google Scholar
  9. [Han93]
    Hanson, E.N., Widom, J. “An Overview of Production Rules in Database Systems”, Knowledge Engineering Review, June, 1993.Google Scholar
  10. [Han92]
    Hanson, E.N. “Rule Condition Testing and Action Execution in Arie 1”, Proc. ACM SIGMOD Conf., 1989.Google Scholar
  11. [Har88]
    Harel, D. “On Visual Formalisms”, CACM, 31:5, May 1988, 514–529.Google Scholar
  12. [Kap91]
    Kappel, G., Schrefl, M. “Object/Behavior Diagrams”, Proc. of 1991 Data Eng. Conf., Kobe, Japan, 530–539.Google Scholar
  13. [Kin84]
    King, R., McLeod, D. “A Unified Model and Methodology for Conceptual Database Design”, in [Bro84], 313–327.Google Scholar
  14. [Kot88]
    Kotz, A.M., Dittrich, K.R., Mulle, J.A. “Supporting Semantic Rules by a Generalized Event/Trigger Mechanism”, Proc. Int. Conf. on Extending Database Tech. Mar. 1988.Google Scholar
  15. [Kun93]
    Kung, D. C. “The Behavior Network Model for Conceptual Information Modeling”, Information Systems, Vol. 18, No. 1, 1993, 1–21.CrossRefGoogle Scholar
  16. [Lav86]
    Lavery, R. G. “Artificial Intelligence and Simulation: An Introduction”, Proc. 1986 Winter Simulation Conf., 448–452.Google Scholar
  17. [Mai86]
    Maier, D., Stein, J., Otis, A., Purdy, A. “Development of an Object-Oriented DBMS”, Proc. OOPSLA'86, Sept. 1986, 472–482.Google Scholar
  18. [McC89]
    McCarthy, D.R., Dayal, U. “The Architecture of an Active Database Management System”, Proc. of ACM SIGMOD Conf., 1989, 215–224.Google Scholar
  19. [Nar93]
    Naranswamy, J., Delcambre, L.M.L., Pollacia, L.F. “Simulation of the Object Flow Model: A Conceptual Modeling Language for Object-Oriented Applications”, Proc. of 26th Simulation Symposium, Washington, D.C., Mar, 1993, 216–225.Google Scholar
  20. [Ngu89]
    Ngu, A. H. H. “Transaction Modeling”, Proc. 5th Int. Conf. Data Eng., 1989, 234–241.Google Scholar
  21. [Peg86]
    Pegden, C. D. “Introduction to SIMAN”, Proc. 1986 Winter Simulation Conf., 95–103.Google Scholar
  22. [Pol93]
    Pollacia, L.F., Delcambre, L.M.L. “The Object Flow Model for Discrete Event Simulation”, Int. Journal in Computer Simulation, Special Issue on Object-Oriented Simulation, Zobrist, G.W. (ed.), Ablex Pub. Norwood, NJ, to appear.Google Scholar
  23. [Pol91]
    Pollacia, L.F. “The Object Flow Model: A Conceptual Modeling Language for Object-Driven Software”, Ph.D. Diss., Univ. of Southwestern LA, Lafayette, LA.Google Scholar
  24. [Pri84]
    Pritsker, A.A.B. Introduction to Simulation and SLAM II, 2nd ed., John Wiley & Sons, New York, 1984.Google Scholar
  25. [Red87]
    Reddy, R. “Epistemology of Knowledge Based Simulation”, Simulation, 48:4, Apr. 1987, 162–166.Google Scholar
  26. [Ros89]
    Rosenthal, A., et al. “Situation Monitoring for Active Databases”, Proc. of 15th VLDB Conf., Amsterdam, The Netherlands, 1989, 455–464.Google Scholar
  27. [Rum91]
    Rumbaugh, J., Blaha, M. Premerplani, W., Eddy, F., Lorensen, W. Object-Oriented Modeling and Design, Prentice-Hall, 1991.Google Scholar
  28. [Sha87]
    Shannon, R. E. “Intelligent Simulation Environments”, Proc. Conf. on Intelligent Simulation Environments, San Diego, Jan. 1986, 150–156.Google Scholar
  29. [Ste84]
    Stemple, D., Sheard, T. “Specification and Verification of Abstract Database Types”, Proc. of the 3rd ACM Symp. on Principles of Database Systems, 1984, 248–257.Google Scholar
  30. [Sto91]
    Stonebraker, M., Kemnitz, G. “The POSTGRES Next Generation Database Management System”, CACM, 34:10, 78–92, Oct. 1991.Google Scholar
  31. [Sto86]
    Stonebraker, M. “Triggers and Inference in Database Systems”, in On Knowledge Base Management Systems, Brodie, Mylopoulos (eds.), Springer Verlag, 1986, 297–314.Google Scholar
  32. [Syb87]
    Sybase, Inc. Transact-SQL User's Guide.Google Scholar
  33. [Wid91]
    Widom, J., Cochrane, R.J., Lindsay, B.G. “Implementing Set-oriented Production Rules as an Extension to Starburst”, Proc. 17th Int'l Conf. on VLDB, Sept. 1991.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Lissa F. Pollacia
    • 1
  • Lois M. L. Delcambre
    • 2
  1. 1.Dept. of Mathematical & Physical SciencesNorthwestern St. Univ.Natchitoches
  2. 2.Computer Science and Engineering Dept.Oregon Graduate InstitutePortland

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