Does enforcing anonymity mean decreasing data usefulness?
Proceedings of the 4th ACM workshop on Quality of protection
A tree-based approach to preserve the privacy of software engineering data and predictive models
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Information Sciences: an International Journal
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Preserving data privacy is posing new challenges to software engineering researchers. Current technologies can be too cumbersome, pervasive or costly to be successfully applied in dynamic and complex scenarios where data exchange occurs among a large number of applications. Anonymization techniques seem to be a promising candidate, even if preliminary investigations suggest that they could deteriorate the quality of data. An empirical study has been carried out in order to understand the relationship between the anonymization level and the degradation of data quality.