Empirical Bayes estimation of software failures

Autores
Barraza, Néstor Rubén
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The empirical Bayes estimator is applied to software failures production. The time between failures data registered up to a given time, are used in order to estimate the probability of failure appearance dur- ing the next interval time. This method is similar to the estimation of n-grams in natural language processing. A modi ed expression to the estimator usually used in language and speech processing is introduced in order to follow the failures production curve. Results of simulations comparing well with experimental data are also shown.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
software reliability
empirical Bayes
growth model
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/41665
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/41665
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Empirical Bayes estimation of software failuresBarraza, Néstor RubénCiencias Informáticassoftware reliabilityempirical Bayesgrowth modelThe empirical Bayes estimator is applied to software failures production. The time between failures data registered up to a given time, are used in order to estimate the probability of failure appearance dur- ing the next interval time. This method is similar to the estimation of n-grams in natural language processing. A modi ed expression to the estimator usually used in language and speech processing is introduced in order to follow the failures production curve. Results of simulations comparing well with experimental data are also shown.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2014-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf11-14http://sedici.unlp.edu.ar/handle/10915/41665enginfo:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/ASSE/01-02-580-2504-2-DR.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2792info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:33:51Zoai:sedici.unlp.edu.ar:10915/41665Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:33:51.368SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Empirical Bayes estimation of software failures
title Empirical Bayes estimation of software failures
spellingShingle Empirical Bayes estimation of software failures
Barraza, Néstor Rubén
Ciencias Informáticas
software reliability
empirical Bayes
growth model
title_short Empirical Bayes estimation of software failures
title_full Empirical Bayes estimation of software failures
title_fullStr Empirical Bayes estimation of software failures
title_full_unstemmed Empirical Bayes estimation of software failures
title_sort Empirical Bayes estimation of software failures
dc.creator.none.fl_str_mv Barraza, Néstor Rubén
author Barraza, Néstor Rubén
author_facet Barraza, Néstor Rubén
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
software reliability
empirical Bayes
growth model
topic Ciencias Informáticas
software reliability
empirical Bayes
growth model
dc.description.none.fl_txt_mv The empirical Bayes estimator is applied to software failures production. The time between failures data registered up to a given time, are used in order to estimate the probability of failure appearance dur- ing the next interval time. This method is similar to the estimation of n-grams in natural language processing. A modi ed expression to the estimator usually used in language and speech processing is introduced in order to follow the failures production curve. Results of simulations comparing well with experimental data are also shown.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description The empirical Bayes estimator is applied to software failures production. The time between failures data registered up to a given time, are used in order to estimate the probability of failure appearance dur- ing the next interval time. This method is similar to the estimation of n-grams in natural language processing. A modi ed expression to the estimator usually used in language and speech processing is introduced in order to follow the failures production curve. Results of simulations comparing well with experimental data are also shown.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/41665
url http://sedici.unlp.edu.ar/handle/10915/41665
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/ASSE/01-02-580-2504-2-DR.pdf
info:eu-repo/semantics/altIdentifier/issn/1850-2792
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
11-14
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.13397

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