July 2016
Beginner to intermediate
408 pages
10h 58m
English
F. Peters Lero - The Irish Software Research Centre, University of Limerick, Limerick, Ireland
One of the facets of data science is reproducible reporting. To do this, data used for analysis must be shared, but this is not always possible due to business sensitivity and/or privacy concerns. In this chapter we share valuable lessons learned from years of data privacy research in the field of Cross Project Defect Prediction. These lessons can be considered when developing or using privacy algorithms for different types of software data.
Data privacy; Data sharing; Cross-project defect prediction; Sensitive attribute disclosure; MORPH; Inverse Privacy ...
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