Title :
Software reliability modeling by concatenating failure rates
Author :
Singpurwalla, Nozer D.
Author_Institution :
George Washington Univ., Washington, DC, USA
Abstract :
The concatenation of failure rate functions results in point process models that need not possess independent increments, or lack memory features of Poisson processes. Processes having a memory are more realistic as compared to those that do not, and as a consequence provide a credible framework for tracking reliability and predicting failure times. The purpose of the paper is to propose and describe a model for software reliability based on this paradigm. The proposed model is adaptive, can explain empirically observed phenomena, and outperforms the predictive ability of its competitors. The model and its inferential mechanism are complex, but software to implement it with ease, is available
Keywords :
Poisson distribution; software quality; software reliability; Poisson processes; empirically observed phenomena; failure rate concatenation; failure rate functions; failure times; inferential mechanism; point process models; predictive ability; software reliability modeling; Concatenated codes; Failure analysis; History; Predictive models; Proposals; Software engineering; Software quality; Software reliability; Stochastic processes;
Conference_Titel :
Software Reliability Engineering, 1998. Proceedings. The Ninth International Symposium on
Conference_Location :
Paderborn
Print_ISBN :
0-8186-8991-9
DOI :
10.1109/ISSRE.1998.730860