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Maximum likelihood estimation for software reliability with masked failure data
College of Computer Science & Information, Guizhou University, Guiyang 550025, China.
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, Industriell ekonomi. Högskolan i Gävle, Centrum för logistik och innovativ produktion.
2013 (kinesisk)Inngår i: Systems engineering and electronics, ISSN 1001-506X, Vol. 35, nr 12, s. 2665-2669Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The masked data are the system failure data when the exact cause of the failures might be unknown. That is, it is the subset of components known to contain the component causing system failures. In general, the maximum likelihood estimation (MLE) of parameters are difficult to find when there exist masked data, because superposition non-homogenous Poisson process (NHPP) software reliability model cannot be decomposed into the independent NHPP models. In this paper, the MLE of software reliability from masked data is studied based on superposition NHPP models. Finally, numerical example based on simulation data is given to illustrate a good performance of MLE.

sted, utgiver, år, opplag, sider
2013. Vol. 35, nr 12, s. 2665-2669
Emneord [en]
masked data, non-homogeneous Poisson process (NHPP), software reliability, maximum likelihood estimation
HSV kategori
Identifikatorer
URN: urn:nbn:se:hig:diva-15489DOI: 10.3969/j.issn.1001-506X.2013.12.34Scopus ID: 2-s2.0-84891954316OAI: oai:DiVA.org:hig-15489DiVA, id: diva2:654684
Tilgjengelig fra: 2013-10-08 Laget: 2013-10-08 Sist oppdatert: 2018-03-13bibliografisk kontrollert

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