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Inference Rules - (BCA / B.Tech)

Inference Rules in DBMS:

Inference Rules are logical rules used to deduce new information from existing facts. In the context of DBMS, they are primarily used to find all possible functional dependencies in a relational database. The most well-known set of inference rules for functional dependencies are Armstrong's Axioms.

Armstrong's Inference Rules for Functional Dependencies:

Given a set of attributes X, Y, Z for a relation:

Reflexivity Rule: If Y is a subset of X, then X → Y (X determines Y). This is a trivial dependency.
Augmentation Rule: If X → Y holds, then XZ → YZ also holds for any set of attributes Z.
Transitivity Rule: If X → Y and Y → Z hold, then X → Z also holds. This is similar to the transitive property in mathematics.

These rules are sound and complete, meaning they can be used to derive all possible functional dependencies from a given set. They are fundamental to database normalization theory.

Inference Rules

Inference Rules in DBMS:

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