Estimativas de máxima verosimilhança e bayesianas do número de erros de um software

• Autor(a) principal: Silva, Karolina Barone Ribeiro da
• Data de Publicação: 2006
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/4498
• topic: Estatística matemática; Processo seqüêncial de captura-recaptura; MSMC; Inferência bayesiana; Estimativas de máxima verosimilhança; Capture-recapture process; Software review; Maximum likelihood estimates; A priori and a posteriori distributions; Bayes estimates; CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA

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.