Reuse refers to a common principle of using existing resources repeatedly, that is pervasively applicable everywhere. In software engineering reuse refers to the development of software systems using already available artifacts or assets partially or completely, with or without modifications. Software reuse not only promises significant improvements in productivity and quality but also provides for the development of more reliable, cost effective, dependable and less buggy (considering that prior use and testing have removed errors) software with reduced time and effort. In this paper we present an efficient and reliable automation model for reusability evaluation of procedure based object oriented software for predicting the reusability levels of the components as low, medium or high. The presented model follows a reusability metric framework that targets the requisite reusability attributes including maintainability (using the Maintainability Index) for functional analysis of the components. Further Multilayer perceptron (using back propagation) based neural network is applied for the establishment of significant relationships among these attributes for reusability prediction. The proposed approach provides support for reusability evaluation at functional level rather than at structural level. The automation support for this approach is provided in the form of a tool named JRA2M2 (Java based Reusability Assessment Automation Model using Multilayer Perceptron (MLP)), implemented in Java. The performance of JRA2M2 is recorded using parameters like accuracy, classification error, precision and recall. The results generated using JRA2M2 indicate that the proposed automation tool can be effectively used as a reliable and efficient solution for automated evaluation of reusability.

Software reuse refers to the development of new software systems with the likelihood of completely or partially using existing components or resources with or without modification. Reusability is the measure of the ease with which previously acquired concepts and objects can be used in new contexts. It is a promising strategy for improvements in software quality, productivity and maintainability as it provides for cost effective, reliable (with the consideration that prior testing and use has eliminated bugs) and accelerated (reduced time to market) development of the software products. In this paper we present an efficient automation model for the identification and evaluation of reusable software components to measure the reusability levels (high, medium or low) of procedure oriented Java based (object oriented) software systems. The presented model uses a metric framework for the functional analysis of the Object oriented software components that target essential attributes of reusability analysis also taking into consideration Maintainability Index to account for partial reuse. Further machine learning algorithm LMNN is explored to establish relationships between the functional attributes. The model works at functional level rather than at structural level. The system is implemented as a tool in Java and the performance of the automation tool developed is recorded using criteria like precision, recall, accuracy and error rate. The results gathered indicate that the model can be effectively used as an efficient, accurate, fast and economic model for the identification of procedure based reusable components from the existing inventory of software resources.