The CCUBE Constraint Object-Oriented Database System

  • Authors:

  • Alexander Brodsky;Victor E. Segal;Jia Chen;Pavel A. Exarkhopoulo

  • Affiliations:

  • Dept. of Information and Software Systems Engineering, George Mason University, Fairfax, VA 22030, USA;Dept. of Information and Software Systems Engineering, George Mason University, Fairfax, VA 22030, USA;Dept. of Information and Software Systems Engineering, George Mason University, Fairfax, VA 22030, USA;Dept. of Information and Software Systems Engineering, George Mason University, Fairfax, VA 22030, USA

  • Venue:
  • Constraints
  • Year:
  • 1998

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Abstract

Constraints provide a flexible and uniform way to representdiverse data capturing spatio-temporal behavior, complex modelingrequirements, partial and incomplete information etc, and havebeen used in a wide variety of application domains. Constraintdatabases have recently emerged to deeply integrate data capturedby constraints in databases. This paper reports on the developmentof the first constraint object-oriented database system, CCUBE,and describes its specification, design and implementation. TheCCUBE system is designed to be used for the implementation andoptimization of high-level constraint object-oriented query languages as well as for directly building software systems requiringextensible use of constraint database features. The CCUBE datamanipulation language, Constraint Comprehension Calculus, isan integration of a constraint calculus for extensible constraintdomains within monoid comprehensions, which serve as an optimization-levellanguage for object-oriented queries. The data model for theconstraint calculus is based on constraint spatio-temporal (CST)objects that may hold spatial, temporal or constraint data, conceptuallyrepresented by constraints. New CST objects are constructed,manipulated and queried by means of the constraint calculus.The model for the monoid comprehensions, in turn, is based onthe notion of monoids, which is a generalization of collectionand aggregation types. The focal point of our work is achievingthe right balance between the expressiveness, complexity andrepresentation usefulness, without which the practical use ofthe system would not be possible. To that end, CCUBE constraintcalculus guarantees polynomial time data complexity, and, furthermore,is tightly integrated with the monoid comprehensions to allowdeeply interleaved global optimization.