Framework for Evaluating Reusability of Procedure Oriented System using Metrics based Approach

In this paper, we present the application of the neural network for the identification of Reusable Software modules in Procedure Oriented Software System. Metrics are used for the structural analysis of the different procedures. The proposed metrics for Procedure oriented paradigm are Cyclometric Complexity Using Mc Cabe’s Measure, Halstead Software Science Indicator, Regularity Metric, Reuse frequency metric, Coupling Metric. The values of these Metrics will become the input dataset for the different neural network systems. Neural Network Based Approach is used to establish the relationship between different attributes of the reusability and serve as the automatic tool for the Evaluation of the reusability of the procedures by calculating the relationship based on its training. Different Eleven Training Algorithms of neural network are experimented and the results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results show that Conjugate