Design by exmple: An application of Armstrong relations
Journal of Computer and System Sciences
Acta Cybernetica
New methods and fast algorithms for database normalization
ACM Transactions on Database Systems (TODS)
On semantic issues connected with keys in relational databases permitting null values
Journal of Information Processing and Cybernetics
Reasoning about functional dependencies generalized for semantic data models
ACM Transactions on Database Systems (TODS)
On the complexity of inferring functional dependencies
Discrete Applied Mathematics - Special issue on combinatorial problems in databases
Algorithms for inferring functional dependencies from relations
Data & Knowledge Engineering
Identifying the Minimal Transversals of a Hypergraph and Related Problems
SIAM Journal on Computing
Asymptotic properties of keys and functional dependencies in random databases
Theoretical Computer Science - Special issue: database theory
Minimum Covers in Relational Database Model
Journal of the ACM (JACM)
Horn clauses and database dependencies
Journal of the ACM (JACM)
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
Entity-Relationship Modeling: Foundations of Database Technology
Entity-Relationship Modeling: Foundations of Database Technology
Synthesizing independent database schemas
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
On Multisets in Database Systems
WMP '00 Proceedings of the Workshop on Multiset Processing: Multiset Processing, Mathematical, Computer Science, and Molecular Computing Points of View
On approximation measures for functional dependencies
Information Systems - Special issue: ADBIS 2002: Advances in databases and information systems
Strong functional dependencies and their application to normal forms in XML
ACM Transactions on Database Systems (TODS)
An information-theoretic approach to normal forms for relational and XML data
Journal of the ACM (JACM)
Database dependency discovery: a machine learning approach
AI Communications
Semantic sampling of existing databases through informative Armstrong databases
Information Systems
Dependency-preserving normalization of relational and XML data
Journal of Computer and System Sciences
Reducing inference control to access control for normalized database schemas
Information Processing Letters
Armstrong axioms and Boyce-Codd-Heath Normal Form under bag semantics
Information Processing Letters
An Introduction to Duplicate Detection
An Introduction to Duplicate Detection
Discover Dependencies from Data—A Review
IEEE Transactions on Knowledge and Data Engineering
Design by example for SQL table definitions with functional dependencies
The VLDB Journal — The International Journal on Very Large Data Bases
Foundations for a fourth normal form over SQL-Like databases
Conceptual Modelling and Its Theoretical Foundations
ACM Transactions on Database Systems (TODS)
APCCM '12 Proceedings of the Eighth Asia-Pacific Conference on Conceptual Modelling - Volume 130
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Classical database theory is largely a theory of relations. Relations are sets of tuples in which no duplicate tuples occur. In practice, duplicate elimination is an operation that is considered to be too expensive in many situations. Fundamental classes of integrity constraints interact differently over bags than they do over relations. This holds for keys and functional dependencies, for example. In this paper, we establish algorithms that compute Armstrong bags for any given set of keys and functional dependencies. These are bags which satisfy the given set of keys and functional dependencies, but violate all keys and functional dependencies not implied by the given set. Armstrong bags perfectly visualize abstract sets of constraints, and can be used by database designers to effectively communicate perceptions or states of a database. Subsequently, we show how existing algorithms to discover functional dependencies in relations can be adapted to discover keys and functional dependencies in bags.