İteratif Yazılım Geliştirme İçin Hata Tahminleme Modeli Araştırma : Bir Durum Çalışması
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One of the biggest problems that software organizations encounter is specifying the resources required and the duration of projects. Organizations that record the number of defects and the effort spent on fixing these defects are able to correctly predict the latent defects in the product and the effort required to remove these latent defects. The use of reliability models reported in the literature is typical to achieve this prediction, but the number of studies that report defect prediction models for iterative software development is scarce. In this thesis, we present a case study which was aimed to predict the defectiveness of new releases in an iterative, civil project where defect arrival phase data is not recorded. With this purpose, we investigated Linear Regression Model and Rayleigh Model, each having their specific statistical distributions, to predict the module level and project level defectiveness of the new releases of an iterative project.