DRCE Maintainability Model for Component Based Systems using Soft Computing Techniques

Abstract

Effective software maintainability is one of the most significant and challenging activity in the field of component based software. Several maintainability models are proposed by the researchers to reduce the maintenance cost, to improve the quality and life span of the software product. The proposed model will assist the software designers to develop maintainable softwares. This paper discusses a maintainability model, which selects four crucial factors that highly affect maintainability of component based software system. Soft computing techniques are employed to demonstrate strong correlation of these factors with maintainability. MATLAB’s Fuzzy logic toolbox is used for predicting the maintainability level of component (such as Excellent, Fair, Good, Bad and worst). Data generated by fuzzy model are provided as input to artificial neural network model. Experimental results shows mean absolute error (MAE) to be .028 and Relative Error (RE) to be .045.To further improve the performance of the model; neuro-fuzzy tool was employed. With the use of self learning capability of this tool, MAE and RE are now improved to the value .0029 and .039. It means that the model was sound enough to provide satisfactory outcomes in comparison to neural network.