An Analysis of Software Reusability Implementation based on Matrix Approach Using Machine Learning

Abstract

Software reusability components not only speed up the development process but also increase the software s reliability. But this reliability and efficiency depend on the number of components used along with interfacing with new components. There is the requirement to study the complexity of the inclusion of these new components in the software system so that the complete software analysis will be performed. In this present work, module component analysis and the integration analysis approach are done to analyze the software system. In this work, a weighted approach is defined to perform the analysis and to identify the effectiveness of software reusability. The Matrix Approach provides the relationship among modules of various software in a structured way. newlineToday most of the available software systems are defined in modular form. These modules are defined in the form of a method or component. As the number of components available on the newlinemarket increases, it is becoming more important to devise software metrics to quantify the various characteristics of components and their usage. Software metrics are intended to newlinemeasure the software quality and performance characteristics quantitatively, encountered during the planning and execution of software development. These can serve as measures of newlinesoftware products for the purpose of comparison, reuse estimation, fault prediction and forecasting. A lot of research has been conducted on software metrics and their applications. newlineMost of the metrics proposed in the literature are based on the source code of the application. However, these metrics cannot be applied to components and component-based systems as the newlinesource code of the components is not available to application developers. Therefore, a different set of metrics is required to measure various aspects for component-based systems and their newlinequality issues. newline