Incomplete Information in Relational Databases
Journal of the ACM (JACM)
Design by exmple: An application of Armstrong relations
Journal of Computer and System Sciences
Functional dependencies and constraints on Null values in database relations
Information and Control
New methods and fast algorithms for database normalization
ACM Transactions on Database Systems (TODS)
Tractable reasoning via approximation
Artificial Intelligence
Axiomatisation of functional dependencies in incomplete relations
Theoretical Computer Science
Extending the database relational model to capture more meaning
ACM Transactions on Database Systems (TODS)
On the Structure of Armstrong Relations for Functional Dependencies
Journal of the ACM (JACM)
A relational model of data for large shared data banks
Communications of the ACM
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Entity-Relationship Modeling: Foundations of Database Technology
Entity-Relationship Modeling: Foundations of Database Technology
Semantic sampling of existing databases through informative Armstrong databases
Information Systems
Functional dependencies in a relational database and propositional logic
IBM Journal of Research and Development
Tractable database design and datalog abduction through bounded treewidth
Information Systems
Characterizing schema mappings via data examples
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
When data dependencies over SQL tables meet the logics of paradox and S-3
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
APCCM '12 Proceedings of the Eighth Asia-Pacific Conference on Conceptual Modelling - Volume 130
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Codd tables are databases that can carry Codd's null "value unknown at present" in columns that are specified as NULL. Under Levene and Loizou's possible world semantics we investigate the combined class of uniqueness constraints and functional dependencies over Codd tables. We characterize the implication problem of this class axiomatically, logically and algorithmically. Since the interaction of members in this class is intricate data engineers can benefit from concise sample tables. Therefore, we investigate structural and computational properties of Armstrong tables. These are Codd tables that satisfy the consequences of a given set of elements in our class and violate all those elements that are not consequences. We characterize when a given Codd table is an Armstrong table for any given set of our class. From this result we establish an algorithm that computes an Armstrong table in time that is at most quadratic in the number of rows in a minimum-sized Armstrong table. Data engineers can use our Armstrong tables to judge, justify, convey and test their understanding of the application domain.