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ICSE 2020
Wed 24 June - Thu 16 July 2020
Tue 7 Jul 2020 08:17 - 08:29 at Goguryeo - I5-Deep Learning Testing and Debugging Chair(s): Pooyan Jamshidi

Although deep neural networks (DNNs) have demonstrated astonishing performance in many applications, there are still concerns on their dependability. One desirable property of DNN for applications with societal impact is fairness (i.e., non-discrimination). In this work, we propose a scalable approach for searching individual discriminatory instances of DNN. Compared with state-of-the-art methods, our approach only employs lightweight procedures like gradient computation and clustering, which makes it significantly more scalable than existing methods. Experimental results show that our approach explores the search space more effectively (9 times) and generates much more individual discriminatory instances (25 times) using much less time (half to 1/7).

Tue 7 Jul
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08:05 - 09:05: I5-Deep Learning Testing and DebuggingPaper Presentations / Technical Papers / Demonstrations at Goguryeo
Chair(s): Pooyan JamshidiUniversity of South Carolina
08:05 - 08:17
Talk
DISSECTOR: Input Validation for Deep Learning Applications by Crossing-layer DissectionTechnical
Technical Papers
Huiyan WangState Key Lab. for Novel Software Tech. and Dept. of Comp. Sci. and Tech., Nanjing University, Nanjing, China, Jingwei XuNanjing University, Chang XuNanjing University, Xiaoxing MaNanjing University, Jian LuNanjing University
08:17 - 08:29
Talk
White-box Fairness Testing through Adversarial SamplingACM SIGSOFT Distinguished Paper AwardsTechnical
Technical Papers
Peixin ZhangZhejiang University, Jingyi WangNational University of Singapore, Singapore, Jun SunSingapore Management University, Guoliang DongComputer College of Zhejiang University, Xinyu WangZhejiang University, Xingen WangZhejiang University, Jin Song DongNational University of Singapore, Dai TingHuawei Corporation
08:29 - 08:32
Talk
FeatureNET: Diversity-driven Generation of Deep Learning ModelsDemo
Demonstrations
Salah GhamiziSntT - University of Luxembourg, Maxime CordySnT, University of Luxembourg, Mike PapadakisUniversity of Luxembourg, Yves Le TraonUniversity of Luxembourg
08:32 - 08:35
Talk
EvalDNN: A Toolbox for Evaluating Deep Neural Network ModelsDemo
Demonstrations
Yongqiang TIANThe Hong Kong University of Science and Technology, Zhihua ZengZhejiang University, Ming WenHuazhong University of Science and Technology, China, Yepang LiuSouthern University of Science and Technology, Tzu-yang KuoThe Hong Kong University of Science and Technology, Shing-Chi CheungDepartment of Computer Science and Engineering, The Hong Kong University of Science and Technology
08:35 - 08:47
Talk
Taxonomy of Real Faults in Deep Learning SystemsACM SIGSOFT Distinguished Artifact AwardsArtifact ReusableTechnicalArtifact Available
Technical Papers
Nargiz HumbatovaUniversità della Svizzera italiana, Gunel JahangirovaUniversità della Svizzera italiana, Gabriele BavotaUniversità della Svizzera italiana, Vincenzo RiccioUniversità della Svizzera italiana, Andrea StoccoUniversità della Svizzera italiana, Paolo TonellaUniversità della Svizzera italiana
08:47 - 08:59
Talk
An Empirical Study on Program Failures of Deep Learning JobsACM SIGSOFT Distinguished Paper AwardsTechnical
Technical Papers
Ru ZhangMicrosoft Research, Wencong XiaoAlibaba, Hongyu ZhangUniversity of Newcastle, Australia, Yu LiuMicrosoft Research, Haoxiang LinMicrosoft Research, Mao YangMicrosoft Research