Which rule defines Boyce-Codd Normal Form (BCNF) and how is it stronger than 3NF?

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Multiple Choice

Which rule defines Boyce-Codd Normal Form (BCNF) and how is it stronger than 3NF?

Explanation:
BCNF hinges on a clear rule about the determinants of dependencies: for every non-trivial functional dependency X -> Y that holds in the relation, X must be a candidate key. A candidate key is a minimal set of attributes that uniquely identifies a row, so when the determinant is a candidate key, the dependency is tied to a key rather than to a non-key attribute. This eliminates dependencies that rely on non-key attributes determining other attributes, which helps prevent update anomalies. This rule makes BCNF stricter than 3NF. In 3NF, you can have a dependency where the left side isn’t a key as long as the right side is a prime attribute (part of some candidate key) or the left side is a superkey. That allowance means 3NF can still permit certain non-key–driven dependencies, whereas BCNF would require decomposing the relation to remove them. In practice, you’d split the relation so that all remaining dependencies have determinants that are keys, resulting in a design with fewer anomalies.

BCNF hinges on a clear rule about the determinants of dependencies: for every non-trivial functional dependency X -> Y that holds in the relation, X must be a candidate key. A candidate key is a minimal set of attributes that uniquely identifies a row, so when the determinant is a candidate key, the dependency is tied to a key rather than to a non-key attribute. This eliminates dependencies that rely on non-key attributes determining other attributes, which helps prevent update anomalies.

This rule makes BCNF stricter than 3NF. In 3NF, you can have a dependency where the left side isn’t a key as long as the right side is a prime attribute (part of some candidate key) or the left side is a superkey. That allowance means 3NF can still permit certain non-key–driven dependencies, whereas BCNF would require decomposing the relation to remove them. In practice, you’d split the relation so that all remaining dependencies have determinants that are keys, resulting in a design with fewer anomalies.

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