Applying reliability models more effectively (software)

A set of linear combination software reliability models that combine the results of single, or component, models is presented. It is shown that, as measured by statistical methods for determining a model's applicability to a set of failure data, a combination model tends to have more accurate short-term and long-term predictions than a component model. These models were evaluated using both historical data sets and data from recent Jet Propulsion Laboratory projects. The computer-aided software reliability estimation (CASRE) tool, which automates many reliability measurement tasks and makes it easier to apply reliability models and to form combination models, is described.>