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A canonical cover ${\displaystyle F_{c}}$ for F (a set of functional dependencies on a relation scheme) is a set of dependencies such that F logically implies all dependencies in ${\displaystyle F_{c}}$, and ${\displaystyle F_{c}}$ logically implies all dependencies in F.

The set ${\displaystyle F_{c}}$ has two important properties:

1. No functional dependency in ${\displaystyle F_{c}}$ contains an extraneous attribute.
2. Each left side of a functional dependency in ${\displaystyle F_{c}}$ is unique. That is, there are no two dependencies ${\displaystyle a\to b}$ and ${\displaystyle c\to d}$ in ${\displaystyle F_{c}}$ such that ${\displaystyle a=c}$.

A canonical cover is not unique for a given set of functional dependencies, therefore one set F can have multiple covers ${\displaystyle F_{c}}$.

Algorithm for computing a canonical cover

1. ${\displaystyle F_{c}=F}$
2. Repeat:
   1. Use the union rule to replace any dependencies in ${\displaystyle F_{c}}$ of the form ${\displaystyle a\to b}$ and ${\displaystyle a\to d}$ with ${\displaystyle a\to bd}$.
   2. Find a functional dependency in ${\displaystyle F_{c}}$ with an extraneous attribute and delete it from ${\displaystyle F_{c}}$
3. ... until ${\displaystyle F_{c}}$ does not change

Canonical cover example

In the following example, F_c is the canonical cover of F.

Given the following, we can find the canonical cover: R = (A, B, C, G, H, I), F = {A→BC, B→C, A→B, AB→C}

1. {A→BC, B→C, A→B, AB→C}
2. {A → BC, B →C, AB → C}
3. {A → BC, B → C}
4. {A → B, B →C}

F_c =  {A → B, B →C}

Extraneous attributes

An attribute is extraneous in a functional dependency if its removal from that functional dependency does not alter the closure of any attributes.

Extraneous determinant attributes

Given a set of functional dependencies ${\displaystyle F}$ and a functional dependency ${\displaystyle A\rightarrow B}$ in ${\displaystyle F}$, the attribute ${\displaystyle a}$ is extraneous in ${\displaystyle A}$ if ${\displaystyle a\subset A}$ and any of the functional dependencies in ${\displaystyle (F-(A\rightarrow B)\cup {(A-a)\rightarrow B})}$ can be implied by ${\displaystyle F}$ using Armstrong's Axioms.

Using an alternate method, given the set of functional dependencies ${\displaystyle F}$, and a functional dependency X → A in ${\displaystyle F}$, attribute Y is extraneous in X if ${\displaystyle Y\subseteq X}$, and ${\displaystyle (X-Y)^{+}\supseteq A}$.

For example:

• If F = {A → C, AB → C}, B is extraneous in AB → C because A → C can be inferred even after deleting B. This is true because if A functionally determines C, then AB also functionally determines C.
• If F = {A → D, D → C, AB → C}, B is extraneous in AB → C because {A → D, D → C, AB → C} logically implies A → C.

Extraneous dependent attributes

Given a set of functional dependencies ${\displaystyle F}$ and a functional dependency ${\displaystyle A\rightarrow B}$ in ${\displaystyle F}$, the attribute ${\displaystyle a}$ is extraneous in ${\displaystyle A}$ if ${\displaystyle a\subset A}$ and any of the functional dependencies in ${\displaystyle (F-(A\rightarrow B)\cup \{A\rightarrow (B-a)\})}$ can be implied by ${\displaystyle F}$ using Armstrong's axioms.

A dependent attribute of a functional dependency is extraneous if we can remove it without changing the closure of the set of determinant attributes in that functional dependency.

For example:

• If F = {A → C, AB → CD}, C is extraneous in AB → CD because AB → C can be inferred even after deleting C.
• If F = {A → BC, B → C}, C is extraneous in A → BC because A → C can be inferred even after deleting C.

References

1. Silberschatz, Abraham (2011). Database system concepts (PDF) (Sixth ed.). New York: McGraw-Hill. ISBN 978-0073523323. Archived from the original (PDF) on 2020-11-08.
2. ^ Elmasri, Ramez (2016). Fundamentals of database systems. Sham Navathe (Seventh ed.). Hoboken, NJ: Pearson. ISBN 978-0-13-397077-7. OCLC 913842106.
3. ^ K, Saravanakumar; asamy. "How to find extraneous attribute? An example". Retrieved 2023-03-14.

• Database theory
• Database algorithms