A neural network approach to software reliability assessment in distributed development environment

At present, software development environment has been changing into new development paradigm in such client/server systems and distributed development by using network computing technologies. Such a paradigm of distributed development will be also used more and more in the period of network computing. Therefore, it is important to assess the reliability of software system in distributed development environment, because the demands for quality and productivity in social systems are on the increase. Many software reliability growth models have been proposed by many researchers. Some of them are actually applied to several software management tools which aid the software quality/reliability assessment and testing-progress control in the testing phase. However, it is difficult to assess the software reliability in recent years, because the complexity of software systems has been increasing as the results of distributed system development. In this paper, we propose a method of software reliability assessment considering the interaction among software components in the system-testing phase of distributed development environment by using neural networks.