Show simple item record

dc.contributor.authorSchneidewind, Norman F.
dc.dateNovember 1993
dc.date.accessioned2015-05-06T00:55:02Z
dc.date.available2015-05-06T00:55:02Z
dc.date.issued1993-11
dc.identifier.citationIEEE Transactions on Software Engineering, Vol. 19, No. 11, November 1993.en_US
dc.identifier.urihttp://hdl.handle.net/10945/45152
dc.description.abstractIn the use of software reliability models it is not necessarily the case that all the failure data should be used to estimate model parameters and to predict failures. The reason for this is that old data may not be as representative of the current and future failure process as recent data. Therefore, it may be possible to obtain more accurate predictions of future failures by excluding or giving lower weight to the earlier failure counts. Although “data aging” techniques such as moving average and exponential smoothing are frequently used in other fields, such as inventory control, we did not find use of data aging in the various models we surveyed. One model that includes the concept of selecting a subset of the failure data is the Schneidewind Non- Homogeneous Poisson Process (NHPP) software reliability model. In order to use the concept of data aging, there must be a criterion for determining the optimal value of the starting failure count interval. We evaluated four criteria for identifying the optimal starting interval for estimating model parameters. Three of the criteria are novel. WOof these treat the failure count interval index as a parameter by substituting model functions for data vectors and optimizing on functions obtained from maximum likelihood estimation techniques. The third one uses weighted least squares to maintain constant variance in the presence of the decreasing failure rate assumed by the model. The fourth criterion is the familiar mean square error. Our research showed that significantly improved reliability predictions can be obtained by using a subset of the failure data, based on applying the appropriate criteria, and using the Space Shuttle On-Board software as an example.en_US
dc.description.sponsorshipThe author wishes to acknowledge the support provided for this project by Dr. W. Farr, Naval Surface Warfare Center; T. Keller, IBM Corporation; and R. Paul, U.S. Army Operational Test and Evaluation Command. The author also acknowledges the mathematical support provided by P. Schneidewind.en_US
dc.publisherIEEEen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleSoftware reliability model with optimal selection of failure dataen_US
dc.typeArticleen_US
dc.contributor.departmentComputer Science (CS)
dc.subject.authorNHPP software reliability modelen_US
dc.subject.authoroptimal selection of failure dataen_US
dc.subject.authorSpace Shuttle applicationen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record