Investigating the predictability of empirical software failure data with artificial neural networks and hybrid models
Date Issued
June 2006
Author(s)
DOI
10.1007/0-387-34224-9_61
Abstract
Software failure and software reliability are strongly related concepts. Introducing a model that would perform successful failure prediction could provide the means for achieving higher software reliability and quality. In this context, we have employed artificial neural networks and genetic algorithms to investigate whether software failure can be accurately modeled and forecasted based on empirical data of real systems. © 2006 International Federation for Information Processing.