A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability X Huang, D Kroening, W Ruan, J Sharp, Y Sun, E Thamo, M Wu
Computer Science Review, 2020
580 2020 Testing deep neural networks Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore
arXiv preprint arXiv:1803.04792, 2018
413 2018 Concolic testing for deep neural networks Y Sun, M Wu, W Ruan, X Huang, M Kwiatkowska, D Kroening
Proceedings of the 33rd ACM/IEEE International Conference on Automated …, 2018
364 2018 Structural test coverage criteria for deep neural networks Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore
ACM Transactions on Embedded Computing Systems (TECS) 18 (5s), 1-23, 2019
142 2019 Global robustness evaluation of deep neural networks with provable guarantees for the hamming distance W Ruan, M Wu, Y Sun, X Huang, D Kroening, M Kwiatkowska
International Joint Conference on Artificial Intelligence, 2019
113 2019 Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models J Chen, J Wang, T Peng, Y Sun, P Cheng, S Ji, X Ma, B Li, D Song
IEEE S&P, 2021
88 2021 DeepConcolic: Testing and debugging deep neural networks Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore
2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019
79 2019 Robot: Robustness-oriented testing for deep learning systems J Wang, J Chen, Y Sun, X Ma, D Wang, J Sun, P Cheng
2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021
78 2021 NNrepair: Constraint-based Repair of Neural Network Classifiers M Usman, D Gopinath, Y Sun, Y Noller, C Pasareanu
CAV 2021, 2021
76 2021 A new era in software security: Towards self-healing software via large language models and formal verification N Tihanyi, R Jain, Y Charalambous, MA Ferrag, Y Sun, LC Cordeiro
arXiv preprint arXiv:2305.14752, 2023
72 2023 Weakly hard schedulability analysis for fixed priority scheduling of periodic real-time tasks Y Sun, MD Natale
ACM Transactions on Embedded Computing Systems (TECS) 16 (5s), 1-19, 2017
61 2017 Coverage-guided testing for recurrent neural networks W Huang, Y Sun, X Zhao, J Sharp, W Ruan, J Meng, X Huang
IEEE Transactions on Reliability 71 (3), 1191-1206, 2021
60 2021 VeriFi : Towards Verifiable Federated UnlearningX Gao, X Ma, J Wang, Y Sun, B Li, S Ji, P Cheng, J Chen
IEEE Transactions on Dependable and Secure Computing, 2024
58 2024 HyDiff: Hybrid differential software analysis Y Noller, CS Păsăreanu, M Böhme, Y Sun, HL Nguyen, L Grunske
Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020
56 2020 Safety and trustworthiness of deep neural networks: A survey X Huang, D Kroening, M Kwiatkowska, W Ruan, Y Sun, E Thamo, M Wu, ...
arXiv preprint arXiv:1812.08342, 151, 2018
50 2018 Explaining Image Classifiers using Statistical Fault Localization Y Sun, H Chockler, X Huang, D Kroening
ECCV, 2020
47 2020 Improving the response time analysis of global fixed-priority multiprocessor scheduling Y Sun, G Lipari, N Guan, W Yi
Embedded and Real-Time Computing Systems and Applications (RTCSA), 2014 IEEE …, 2014
41 2014 Building better bit-blasting for floating-point problems M Brain, F Schanda, Y Sun
Tools and Algorithms for the Construction and Analysis of Systems: 25th …, 2019
38 2019 Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the W Ruan, M Wu, Y Sun, X Huang, D Kroening, M Kwiatkowska
arXiv preprint arXiv:1804.05805, 2018
37 2018 On the ineffectiveness of 1/m-based interference bounds in the analysis of global EDF and FIFO scheduling A Biondi, Y Sun
Real-Time Systems 54, 515-536, 2018
31 2018 