000186762 001__ 186762
000186762 005__ 20190316235635.0
000186762 037__ $$aCONF
000186762 245__ $$aMitigating Anonymity Challenges in Automated Testing and Debugging Systems
000186762 269__ $$a2013
000186762 260__ $$c2013
000186762 336__ $$aConference Papers
000186762 520__ $$aModern software often provides automated testing and bug reporting facilities that enable developers to improve the software after release. Alas, this comes at the cost of user anonymity: reported execution traces may identify users. We present a way to mitigate this inherent tension between developer utility and user anonymity: automati- cally transform execution traces in a way that preserves their utility for testing and debugging while, at the same time, providing k-anonymity to users, i.e., a guarantee that the trace can at most identify the user as being part of a group of k indistinguishable users. We evaluate this approach in the context of an automated testing and bug reporting system for smartphone applications.
000186762 700__ $$0243537$$g184038$$aAndrica, Silviu
000186762 700__ $$0241982$$g172241$$aCandea, George
000186762 7112_ $$dJune 26-28, 2013$$cSan Jose, CA, USA$$a10th International Conference on Autonomic Computing
000186762 8564_ $$uhttps://infoscience.epfl.ch/record/186762/files/main.pdf$$zn/a$$s159527$$yn/a
000186762 909C0 $$xU11275$$0252225$$pDSLAB
000186762 909CO $$qGLOBAL_SET$$pconf$$ooai:infoscience.tind.io:186762$$pIC
000186762 917Z8 $$x184038
000186762 937__ $$aEPFL-CONF-186762
000186762 973__ $$rREVIEWED$$sACCEPTED$$aEPFL
000186762 980__ $$aCONF