Relational Database Schema Designer: CASE tool Teaching Aid for Bernstein’s Algorithm

02 April 2015CS4221 project presentation - by Group 03Liu Wei RanLu NanWu LongZhao Yue

Agenda

• Objective

• Bernstein’s Algorithm and its shortcomings

• Implementation

• New Features

• Future work

• Demo

Objective

• Implementation of enhanced Bernstein’s Algorithm

• Teaching aid with interactive user interface

Bernstein’s Algorithm

• Bernstein’s Algorithm was invented by Bernstein Philip in 1976

• The algorithm consists of 6 steps

• Produce 3NF with the fewest number of relations

Bernstein’s Algorithm

Given a relational schema R and a set of functional dependencies F

Step 1: Eliminate extraneous attributes from the left side of each FD in F to produce G.

Step 2: Find a non-redundant covering of G.

Step 3: Partition G into groups such that all FDs have identical left side in each group.

Step 4: Merge equivalent keys if left sides have the bijection relation to create J.

Step 5: Eliminate transitive dependencies.

Step 6: Construct relation consisting of all the attributes appearing in each group.

Shortcomings

1. It does not guarantee losslessness.

2. It does not find all the keys.

3. It does not remove all the superfluous attributes.

4. Relations produced depends on the non-redundant covering found.

5. BCNF schema may contain superfluous attributes.

Implementation

Step 1

• [find_minimal_cover] : Step one and two, eliminate extraneous attributes and find

covering.

• INPUT : <__G>, the set of functional dependencies

• RETURN : <__H>, the minimum cover of the input functional dependencies

Implementation

Step 2

• [partition] : Step three, partition the minimum cover <__H> into groups that has

identical left sides

• INPUT : <__H>, the minimum cover

• RETURN : <__partitioned_fds_list>, all the groups of partitioned functional

dependency list

Implementation

Step 3

• [merge_keys] : Step four, merge equivalent keys.

• INPUT : <__partitioned_fds_list> and <__H>

• RETURN : <__merged_fds_list>, all merged groups of functional dependency list

Implementation

Step 4

• [eliminate_transitive_fds] : Step five, find and remove transitive dependencies for the

input.

• INPUT : <__merged_fds_list>

• RETURN : <__final_fds_list>, the finalized group of functional dependency list

Implementation

Step 5

• [contruct_relations] : Step six, construct relational schema for each groups.

• INPUT : <__final_fds_list>

• RETURN : <__relations>, all the relational schemas

New Features

1.Losslessness Checker

2.Superfluous Attribute Checker

3.Candidate Key Finder

Losslessness Checker

AB -> CD, A -> CD

Schema A C B D

['A', 'C', 'D'] 1 1 0 1

Candidate Key Finder

AD -> B, B -> C, C -> D, AB -> E, AC -> F

Left Middle Right

[‘A’] [‘B’, ‘C’, ‘D’] [‘E’, ‘F’]

‘A’, ‘AB’, ‘AC’, ‘AD’, ‘ABC’, ‘ABD’, ‘ACD’

Superfluous Attribute Checker

[superfluous_attribute_detection_algorithm] : Check whether a given attribute is a

superfluous in a relational schema.

INPUT :

<relations> : The input relational schemas

<G> : The original functional dependency list

<test_relation> : A relation that is in the input relational schemas <relations>

<test_attribute> : The attribute that need to be tested for <test_relation>

RETURN : True if the <test_attribute> is superfluous in <test_relation>, False if it is not

Future work

• UI improvement

• Solve shortcoming 4 by using superfluous attribute checker to check

every attributes in all possible covers found, to get the best relations

results.

Demo

Q&APresentation by

Zhao YueWu Long

Liu Wei RanLu Nan

Thank You!Presentation by

Zhao YueWu Long

Liu Wei RanLu Nan