Blogs (1) >>
ICSE 2019
Sat 25 - Fri 31 May 2019 Montreal, QC, Canada
Fri 31 May 2019 15:10 - 15:20 at Place du Canada - Testing of AI Systems Chair(s): Marija Mikic

There is a dramatically increasing interest in the quality assurance for DNN-based systems in the software engineering community. An emerging hot topic in this direction is structural coverage criteria for testing neural networks, which are inspired by coverage metrics used in conventional software testing. In this short paper, we argue that these criteria could be misleading because of the fundamental differences between neural networks and human written programs. Our preliminary exploration shows that (1) adversarial examples are pervasively distributed in the finely divided space defined by such coverage criteria, while available natural samples are very sparse, and as a consequence, (2) previously reported fault-detection “capabilities” conjectured from high coverage testing are more likely due to the adversary-oriented search but not the real “high” coverage.

Fri 31 May
Times are displayed in time zone: Eastern Time (US & Canada) change

14:00 - 15:30: Testing of AI SystemsPapers / New Ideas and Emerging Results / Demonstrations / Technical Track at Place du Canada
Chair(s): Marija MikicGoogle
14:00 - 14:20
Talk
CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning LibrariesTechnical Track
Technical Track
Viet Hung PhamUniversity of Waterloo, Thibaud Lutellier, Weizhen QiUniversity of Science and Technology of China, Lin TanPurdue University
Pre-print
14:20 - 14:40
Talk
Guiding Deep Learning System Testing using Surprise AdequacyArtifacts AvailableArtifacts Evaluated ReusableResults ReproducedTechnical Track
Technical Track
Jinhan KimKAIST, Robert FeldtChalmers University of Technology, Shin YooKorea Advanced Institute of Science and Technology
Authorizer link Pre-print
14:40 - 15:00
Talk
DeepConcolic: Testing and Debugging Deep Neural NetworksDemos
Demonstrations
Youcheng SunUniversity of Oxford, Xiaowei HuangUniversity of Liverpool, Daniel KroeningUniversity of Oxford, James SharpDefence Science and Technology Laboratory (Dstl), Matthew HillDefence Science and Technology Laboratory (Dstl), Rob AshmoreDefence Science and Technology Laboratory (Dstl)
15:00 - 15:10
Talk
Towards Improved Testing For Deep LearningNIER
New Ideas and Emerging Results
Jasmine SekhonUniversity of Virginia, Cody FlemingUniversity of Virginia
Pre-print
15:10 - 15:20
Talk
Structural Coverage Criteria for Neural Networks Could Be MisleadingNIER
New Ideas and Emerging Results
Zenan LiNanjing University, Xiaoxing MaNanjing University, Chang XuNanjing University, Chun CaoNanjing University
Pre-print
15:20 - 15:30
Talk
Robustness of Neural Networks: A Probabilistic and Practical PerspectiveNIER
New Ideas and Emerging Results
Ravi MangalGeorgia Institute of Technology, Aditya Nori, Alessandro OrsoGeorgia Tech