Comparison of software reliability assessment methods based on neural network for distributed development environment

A computer-software is developed by human work, therefore many software faults must be introduced into the software product during the development process. Moreover, they may cause serious accidents affecting people's lives. Especially, software development environment has been changing into new development paradigm in such client/server systems and distributed development by using network computing technologies. Therefore, it is difficult to assess the software reliability in recent years, because the complexity of software systems has been increasing as the result of distributed system development. In this paper, we compare our software reliability assessment method by using neural network with several conventional software reliability assessment methods in terms of goodness-of-fit for actual data, and consider the validity as a software reliability assessment method in distributed development environment.