A hybrid approach for the prediction of fault proneness in object oriented design using fuzzy logic

Empirical studies conducted by the researchers on object-oriented design metrics are useful for forecasting the fault-proneness of classes in object-oriented design. In this study, we propose an integrated hybrid model to empirically investigate the fault-proneness of object-oriented design. We will use a subset of the Chidamber and Kemerer suite and all of the MOOD metrics to predict fault-proneness of object oriented design. Moreover with the increasing demand for quality software there is an increase in metrics which can measure OO attributes such as coupling, cohesion and inheritance. Therefore, there is a need for quality models that investigate the association between these properties and quality attributes such as fault proneness, maintainability, extendibility, effectiveness or productivity, to be able to use the metrics effectively and efficiently. The aim of this study is to empirically investigate the association between object oriented design metrics and fault proneness of object oriented systems.