Main Article Content
Software reuse is the process of implementing or updating software systems using existing software assets. Software Reuse promises
significant improvements in software productivity and quality. There are two approaches for reuse of code: develop the code from scratch or identify
and extract the reusable code from already developed codes. A great deal of research over the past several years has been devoted to the development
of methodologies to create reusable software components and component libraries, where there is an additional cost involved to create a reusable
component from scratch. But the issue of how to identify good reusable components from existing systems has remained relatively unexplored. Our
approach, for identification and evaluation of reusable software, is based on software models and metrics. As the exact relationship between the
attributes of the reusability is difficult to establish so a Clustering Based approach could serve as an economical, automatic tool to generate
reusability ranking of software by formulating the relationship based on its training. The Kmeans based clustering has proved its effectiveness in
modeling of data in various domains. Inputs to the clustering system, are provided in form of McCabeâ€™s Cyclometric Complexity Measure for
Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling
Metric values of the software component and output is be obtained in terms of reusability.This Approach is applied on the C based software
modules/components and it can further be extended to the Artificial Intelligence (AI) based software components e.g. Prolog Language based
software components. It can also be tried to calculate the fault-tolerance of the software components with help of the proposed metric framework.
Keywords: Reuse, clustering, metric, cyclometric, complexity, coupling etc.
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