Using Fuzzy Logic to Evaluate Normalization Completeness for an Improved Database Design

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M. Rizwan Jameel Qureshi 1,* Mahaboob Sharief Shaik 1 Nayyar Iqbal 2

1. Faculty of Computing & Information Technology of King Abdul Aziz University, Jeddah, Saudi Arabia

2. Department of Computer Science of Agricultural University, Faisalabad, Pakistan

* Corresponding author.


Received: 27 Mar. 2011 / Revised: 3 Aug. 2011 / Accepted: 20 Oct. 2011 / Published: 8 Mar. 2012

Index Terms

Normalization completeness, Conceptual model, Relation, Functional dependency, Total attributes, Completeness attributes, Preventing attributes


A new approach, to measure normalization completeness for conceptual model, is introduced using quantitative fuzzy functionality in this paper. We measure the normalization completeness of the conceptual model in two steps. In the first step, different normalization techniques are analyzed up to Boyce Codd Normal Form (BCNF) to find the current normal form of the relation. In the second step, fuzzy membership values are used to scale the normal form between 0 and 1. Case studies to explain schema transformation rules and measurements. Normalization completeness is measured by considering completeness attributes, preventing attributes of the functional dependencies and total number of attributes such as if the functional dependency is non-preventing then the attributes of that functional dependency are completeness attributes. The attributes of functional dependency which prevent to go to the next normal form are called preventing attributes.

Cite This Paper

M. Rizwan Jameel Qureshi, Mahaboob Sharief Shaik, Nayyar Iqbal, "Using Fuzzy Logic to Evaluate Normalization Completeness for an Improved Database Design", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.2, pp.48-55, 2012. DOI:10.5815/ijitcs.2012.02.07


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