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Prediction of software defects works well within projects as long as there is a sufficient amount of data available to train any models. However, this is rarely the case for new software projects and for many companies. So far, only a few have studies focused on transferring prediction models from one project to another. In this paper, we study cross-project defect prediction models on a large scale. For 12 real-world applications, we ran 622 cross-project predictions. Our results indicate thatdoi:10.1145/1595696.1595713 dblp:conf/sigsoft/ZimmermannNGGM09 fatcat:ukpls5z66ncsri75n4ebpgnysm