dc.creatorBarraza, Néstor Rubén
dc.date2016-09
dc.date2016-12-02
dc.date2016-12-02T16:50:08Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/57254
dc.identifierhttp://45jaiio.sadio.org.ar/sites/default/files/asse-16.pdf
dc.identifierissn:2451-7593
dc.descriptionSoftware Reliability models has been developed for decades. The majority of them are based on non homogeneous Poisson processes, where the failure rate is a non linear function of time. They are also well described by pure birth processes what leads to non homogeneous continuous time Markov chains (NHCTMC), as it is usually used in the simulation of the stochastic software failure process. We propose in this work a different and novel approach. We consider a failure rate that does not depend on time but depends non linearly on the number of failures λr(t) = λr. We use the parametric Empirical Bayes framework in order to estimate λr.
dc.descriptionSociedad Argentina de Informática e Investigación Operativa (SADIO)
dc.formatapplication/pdf
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-sa/3.0/
dc.rightsCreative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
dc.subjectCiencias Informáticas
dc.subjectsoftware reliability models
dc.subjectfailure rate
dc.titleA New Homogeneous Pure Birth Process based Software Reliability Model
dc.typeObjeto de conferencia
dc.typeResumen


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