Modeling of Reusability of Procedure based Software Components using Naive Bayes Classifier Approach

Abstract

We have developed a highly flexible module to evaluate and access the reusability of software components. The purpose of this model is to do pattern recognition by discovering supervised features which can help us to measure the intangible aspects of software components in terms of reusability. There were several function based applications which were given due diligence for identifying their various degrees of reusability of their components. Once these projects were analyzed their software components were measured in terms of software metrics including (Volume, Coupling, Complexity, Reuse frequency, Regularity and Reusability). These measured metrics were carefully allocated a particular set of label which was based on the principals of software engineering and objectives to be achieved for doing the due research. Therefore, in this research work we are studying the degree of reusability by using six classes Naive Bayes Classification method which was able to give high precision value as compare to previous methods.