Estimativas de máxima verosimilhança e bayesianas do número de erros de um software.
AUTOR(ES)
Karolina Barone Ribeiro da Silva
DATA DE PUBLICAÇÃO
2006
RESUMO
In this work we present the methodology of capture-recapture, under the classic and bayesian approach, to estimate the number of errors of software through inspection by distinct reviewers. We present the general statistical model considering independence among errors and among reviewers and consider the particular cases of equally detectable errors (homogeneous) and reviewers not equally e cient (heterogeneous) and of errors not equally detectable (heterogeneous) and equally e cient reviewers (homogeneous). After that, under the assumption of independence and heterogeneity among errors and independence and homogeneity among reviwers, we supposed that the heterogeneity of the errors was expressed by a classification of these in easy and di cult of detecting, admitting known the probabilities of detection of an easy error and of a di cult error. Finally, under the hypothesis of independence and homogeneity among errors, we presented a new model considering heterogeneity and dependence among reviewers. Besides, we presented examples with simulate and real data.
ASSUNTO(S)
estimativas de máxima verosimilhança a priori and a posteriori distributions software review msmc estatística matemática estatistica bayes estimates processo seqüêncial de captura-recaptura capture-recapture process inferência bayesiana maximum likelihood estimates
