Abstract
Most software reliability growth models work under the assumption that reliability of software grows due to the removal of bugs that cause failures. However, another phenomenon has often been observed—the failure rate of a software product following its release decreases with time even if no bugs are corrected. In this article we present a simple model to represent this phenomenon. We introduce the concept of initial transient failure rate of the product and assume that it decays with a factor α per unit time thereby increasing the product reliability with time. When the transient failure rate decays away, the product displays a steady state failure rate. We discuss how the parameters in this model—initial transient failure rate, decay factor, and steady state failure rate—can be determined from the failure and sales data of a product. We also describe how, using the model, we can determine the product stabilization time—a product quality metric that describes how long it takes a product to reach close to its stable failure rate. We provide many examples where this model has been applied to data from released products.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ACM Transactions on Software Engineering and Methodology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
