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Negative binomial regression has been proposed as an approach to predicting fault-prone software modules. However, little work has been reported to study the strength, weakness, and applicability of this method. In this paper, we present a deep study to investigate the effectiveness of using negative binomial regression to predict fault-prone software modules under two different conditions, selfassessment and forward assessment. The performance of negative binomial regression model is alsodoi:10.5815/ijitcs.2012.08.08 fatcat:w2uo7cnvijaqtopudr6cs62nmm