Estimating Reliability of Component Based Software Using Artificial Neural Network and Fuzzy Logic

To estimate the reliability of software various reliability growth models have been proposed but no one is proven to be best for various applications. Component Based Systems achieve flexibility by clearly separating the stable parts of systems (i.e. the components) from the specification of their composition. In order to estimate the reliability of Component Based Software System, it is required to measure the reliability of each component of the system. However, due to the black-box nature of components, where the source code of these components are not available, it is difficult to use conventional metrics in Component Based Development as these metrics require analysis of source codes. Soft Computing Techniques i.e. Artificial Neural Networks and Fuzzy Logic have been recognized as attractive alternatives to the standard, well-established “hard computing” paradigms. In this paper, we adopt Soft Computing Techniques i.e. Artificial Neural Networks and Fuzzy Logic based approach to estimate the reliability of Component Based Software, the reliability of Component Based Software will be estimated based on the reliabilities of the individual components and the architecture of the system.