Cross-project Defect Prediction – ESEC/FSE 2009

by Thomas Zimmermann, Nachiappan Nagappan, Harald Gall, Emanuel Giger, Brendan Murphy

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 that cross-project prediction is a serious challenge, i.e., simply using models from projects in the same domain or with the same process does not lead to accurate predictions. To help software engineers choose models wisely, we identified factors that do influence the success of cross-project predictions. We also derived decision trees that can provide early estimates for precision, recall, and accuracy before a prediction is attempted.

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Reference

Thomas Zimmermann, Nachiappan Nagappan, Harald Gall, Emanuel Giger, Brendan Murphy. Cross-project Defect Prediction. In Proceedings of the 7th joint meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE 2009), Amsterdam, The Netherlands, August 2009.

BibTeX Entry

@inproceedings{zimmermann-esecfse-2009,
    title = "Cross-project Defect Prediction",
    author = "Thomas Zimmermann and Nachiappan Nagappan and Harald Gall and Emanuel Giger and Brendan Murphy",
    year = "2009",
    month = "August",
    booktitle = "Proceedings of the 7th joint meeting of the European Software Engineering Conference and the ACM
SIGSOFT Symposium on the Foundations of Software Engineering",
    location = "Amsterdam, The Netherlands",
    publisher = "ACM",
}