Hierarchical Self Organizing Maps for Reusability Measurement and Performance Metrics Assessment of Software Components

In the product business, it is fundamental that reduction time and endeavors in programming
improvement. Programming reusability is a significant measure to improve the advancement and
nature of programming. Improving reusability will diminish conveyance time of programming items,
diminishes the improvement exertion and furthermore programming mistakes and cost of
advancement procedure. Programming reuse is the best arrangement factor to secure the current
information from the programming distribution warehouse. Estimating the reusability level of the
product is fundamental to accomplish the objectives of reuse. Information mining is the way toward
extracting helpful patterns and breakdown data sets from huge information collections. The reusability
of a product segment picks the correct estimation and upgrades the certainty of a function for reuse.
The software metrics are utilized as quantitative measures to set up and assess the parts. In this
paper estimating the product reusability utilizing several classification algorithms on a particular
programming reuse data set are connected. The framework is actualized utilizing the R information
mining tool and execution of the computerized framework is created for reusability expectation like
accuracy, review, f-measure. The test result demonstrates the representation can be viably utilized
wasteful, precise, and speedier and is financial for distinguishing proof of reusable parts from the
current programming assets. This document seeks to gives comparative analysis of H-SOM and
Naïve Bayes algorithm classifiers of Dengue datasets.