LACE2- Better Privacy-Preserving Data Sharing for Cross Project Defect Prediction
with Fayola Peters, Lero, Irish SE Research Centre
Before a community can learn general principles, it must share individual experiences. A wide range of privacy con- siderations complicates sharing of data in software engineering. Prior work on secure data sharing allowed data owners to share their data on a single-party basis.
LACE2 extends that work by considering multi-party data sharing where data owners incrementally add data to a cache passed between them. Only a portion of local data is added to this cache: the “interesting” data that are not similar to the current contents of the cache. Also, before data owner i passes the cache to data owner j, privacy is preserved by applying obfuscation algorithms to hide project details.
The experiments of this research show that (a) LACE2 is comparatively less expensive than the single-party approach and (b) the multi-party approach of LACE2 yields higher privacy than the prior approach without damaging predictive power (indeed, in some cases, LACE2 lead to better defect predictors).