A Novel Software Component Selection Through Statistical Models

Software components are the inevitable commodity for all web pages to provide bountiful services. The objective of the reusable Software Component couplings and cohesions helps in providing big services to the web pages and acting as a backbone. In the study 82% of the commercial components play a vital role and remaining percentage are considered here as customized components. Components interoperability is possible via intra-inter components. Customized components are economical in nature and the above said components can be utilized for the empirical applications. Selection towards components and identifying software components for design needs extraordinary methodologies and techniques employed like Classifications, Clustering and Associations provide a greater mileage and milestone for above mentioned methodology. The applied methodologies were Rank order for clustering; k-means clustering and similarity based coefficients. The result of the study shows the selecting the best software components for web applications. The research work concludes reusable software components are providing better services to the web applications at a affordable price.