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

Displayed time zone: Eastern Time (US & Canada) change

14:00 - 15:30
14:00
20m
Talk
CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning LibrariesTechnical Track
Technical Track
Viet Hung Pham University of Waterloo, Thibaud Lutellier , Weizhen Qi University of Science and Technology of China, Lin Tan Purdue University
Pre-print
14:20
20m
Talk
Guiding Deep Learning System Testing using Surprise AdequacyArtifacts AvailableArtifacts Evaluated ReusableResults ReproducedTechnical Track
Technical Track
Jinhan Kim KAIST, Robert Feldt Chalmers University of Technology, Shin Yoo Korea Advanced Institute of Science and Technology
Authorizer link Pre-print
14:40
20m
Talk
DeepConcolic: Testing and Debugging Deep Neural NetworksDemos
Demonstrations
Youcheng Sun University of Oxford, Xiaowei Huang University of Liverpool, Daniel Kroening University of Oxford, James Sharp Defence Science and Technology Laboratory (Dstl), Matthew Hill Defence Science and Technology Laboratory (Dstl), Rob Ashmore Defence Science and Technology Laboratory (Dstl)
15:00
10m
Talk
Towards Improved Testing For Deep LearningNIER
New Ideas and Emerging Results
Jasmine Sekhon University of Virginia, Cody Fleming University of Virginia
Pre-print
15:10
10m
Talk
Structural Coverage Criteria for Neural Networks Could Be MisleadingNIER
New Ideas and Emerging Results
Zenan Li Nanjing University, Xiaoxing Ma Nanjing University, Chang Xu Nanjing University, Chun Cao Nanjing University
Pre-print
15:20
10m
Talk
Robustness of Neural Networks: A Probabilistic and Practical PerspectiveNIER
New Ideas and Emerging Results
Ravi Mangal Georgia Institute of Technology, Aditya Nori , Alessandro Orso Georgia Tech