Redundancy in functional databases

doi:10.1016/0306-4379(86)90030-X

Information Systems

Volume 11, Issue 3, 1986, Pages 225-234

https://doi.org/10.1016/0306-4379(86)90030-X Get rights and content

Abstract

A set of axioms are presented to algebraically derive implied redundancies in functional databases. The axioms are proved to be sound with respect to the definitions of operators. The functional granularity concept is introduced and shown to be crucial in derivations.

References (12)

L. Orman
A familial model of data for multilevel schema framework
Inform. Systems
(1982)
D. Shipman
The functional data model and the data language DAPLEX
ACM Trans. Database Systems
(1981)
L. Orman
Design criteria for functional databases
Inform. Systems
(1985)
D. Maier et al.
On the foundations of the universal relation model
ACM Trans. Database Systems
(1984)
A.V. Aho et al.
The theory of joins in relational databases
ACM Trans. Database Systems
(1979)
E. Sciore
A complete axiomatization of full join dependencies
J. ACM
(1982)

There are more references available in the full text version of this article.

Cited by (1)

Proof procedures for detecting redundancy of database constraints
1989, Information and Software Technology
A production-rule-based notation is introduced to express and manipulate database constraints. Two proof procedures are developed to detect the redundancy of database constraints. The direct proof procedure is human oriented and based on natural deduction. Human-oriented proof procedures are important as most data-model design is still done manually and nonredundancy of database constraints is the major determinant of a good design. The indirect proof procedure is machine oriented. It involves conversion of the production rules to the clausal form of first-order logic and resolution theorem proving. Machine-oriented proof procedures are important as many proofs are cumbersome and beyond the time and complexity tolerance of data-model designers. Using the same notation to facilitate both human and machine proof procedures is useful in facilitating human-machine interaction in data-model design. Both procedures are general enough to be used with a variety of data models, including relational and functional models. The applicability of the procedures to a variety of data models is useful in multidatabase environments and in exploring concepts that are common to many data models.

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Information Systems

Redundancy in functional databases

Abstract

A familial model of data for multilevel schema framework

Inform. Systems

The functional data model and the data language DAPLEX

ACM Trans. Database Systems

Design criteria for functional databases

Inform. Systems

On the foundations of the universal relation model

ACM Trans. Database Systems

The theory of joins in relational databases

ACM Trans. Database Systems

A complete axiomatization of full join dependencies

J. ACM

Proof procedures for detecting redundancy of database constraints