DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars

28 August 2017

Papers citing "DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars"

50 / 145 papers shown

Title
Safety Interventions against Adversarial Patches in an Open-Source Driver Assistance System Cheng Chen Grant Xiao Daehyun Lee Lishan Yang E. Smirni H. Alemzadeh Xugui Zhou AAML 31 1 0 26 Apr 2025
Towards Assessing Deep Learning Test Input Generators Seif Mzoughi Ahmed Hajyahmed Mohamed Elshafei Foutse Khomh anb Diego Elias Costa D. Costa AAML 40 0 0 03 Apr 2025
Online Controller Synthesis for Robot Collision Avoidance: A Case Study Yuheng Fan Wang Lin 49 0 0 08 Feb 2025
Path Analysis for Effective Fault Localization in Deep Neural Networks Soroush Hashemifar Saeed Parsa A. Kalaee AAML 44 0 0 28 Jan 2025
Improving DNN Modularization via Activation-Driven Training Tuan Ngo Abid Hassan Saad Shafiq Nenad Medvidovic MoMe 32 0 0 01 Nov 2024
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers Lam Nguyen Tung Steven Cho Xiaoning Du Neelofar Neelofar Valerio Terragni Stefano Ruberto Aldeida Aleti 201 2 0 30 Oct 2024
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification Ruben Grewal Paolo Tonella Andrea Stocco 48 12 0 29 Apr 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward Xuan Xie Jiayang Song Zhehua Zhou Yuheng Huang Da Song Lei Ma OffRL 53 6 0 12 Apr 2024
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving Shahin Atakishiyev Mohammad Salameh Randy Goebel 72 6 0 18 Mar 2024
Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning Jingxuan Yang Ruoxuan Bai Haoyuan Ji Yi Zhang Jianming Hu Shuo Feng 37 3 0 29 Feb 2024
Beyond Accuracy: An Empirical Study on Unit Testing in Open-source Deep Learning Projects Han Wang Sijia Yu Chunyang Chen Burak Turhan Xiaodong Zhu ELM MLAU 25 2 0 26 Feb 2024
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems A Case Study Hala Abdelkader Mohamed Abdelrazek Scott Barnett Jean-Guy Schneider Priya Rani Rajesh Vasa 40 3 0 12 Jan 2024
Machine Translation Testing via Syntactic Tree Pruning Quanjun Zhang Juan Zhai Chunrong Fang Jiawei Liu Weisong Sun Haichuan Hu Qingyu Wang 28 3 0 01 Jan 2024
Sensitive Region-based Metamorphic Testing Framework using Explainable AI Yuma Torikoshi Y. Nishi Juichi Takahashi 30 2 0 14 Mar 2023
Greener yet Powerful: Taming Large Code Generation Models with Quantization Xiaokai Wei Sujan Kumar Gonugondla W. Ahmad Shiqi Wang Baishakhi Ray ... Ben Athiwaratkun Mingyue Shang M. K. Ramanathan Parminder Bhatia Bing Xiang MQ 30 6 0 09 Mar 2023
DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks Zohreh Aghababaeyan Manel Abdellatif Mahboubeh Dadkhah Lionel C. Briand AAML 34 16 0 08 Mar 2023
Safe Robot Learning in Assistive Devices through Neural Network Repair K. Majd Geoffrey Clark Tanmay Khandait Siyu Zhou S. Sankaranarayanan Georgios Fainekos H. B. Amor 27 1 0 08 Mar 2023
OccRob: Efficient SMT-Based Occlusion Robustness Verification of Deep Neural Networks Xingwu Guo Ziwei Zhou Yueling Zhang Guy Katz Hao Fei AAML 37 5 0 27 Jan 2023
Understanding the Complexity and Its Impact on Testing in ML-Enabled Systems Junming Cao Bihuan Chen Longjie Hu Jie Ying Gao Kaifeng Huang Xin Peng 26 3 0 10 Jan 2023
FedDebug: Systematic Debugging for Federated Learning Applications Waris Gill A. Anwar Muhammad Ali Gulzar FedML 31 11 0 09 Jan 2023
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study Vincenzo Riccio Paolo Tonella AAML 24 29 0 21 Dec 2022
QEBVerif: Quantization Error Bound Verification of Neural Networks Yedi Zhang Fu Song Jun Sun MQ 26 11 0 06 Dec 2022
An Empirical Study of Library Usage and Dependency in Deep Learning Frameworks Mohamed Raed El aoun L. Tidjon Ben Rombaut Foutse Khomh Ahmed E. Hassan 27 5 0 28 Nov 2022
DriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing Seulbae Kim Major Liu J. Rhee Yuseok Jeon Yonghwi Kwon C. Kim 27 43 0 25 Oct 2022
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks Jiyang Guan Jian Liang Ran He AAML MLAU 50 29 0 21 Oct 2022
Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks Shengming Yuan Qilong Zhang Lianli Gao Yaya Cheng Jingkuan Song AAML 24 42 0 05 Oct 2022
Perception Simplex: Verifiable Collision Avoidance in Autonomous Vehicles Amidst Obstacle Detection Faults Ayoosh Bansal Hunmin Kim Simon Yu Bo-wen Li N. Hovakimyan Marco Caccamo L. Sha AAML 37 4 0 04 Sep 2022
Verifiable Obstacle Detection Ayoosh Bansal Hunmin Kim Simon Yu Bo-Yi Li N. Hovakimyan Marco Caccamo L. Sha 28 6 0 30 Aug 2022
Mixed-Precision Neural Networks: A Survey M. Rakka M. Fouda Pramod P. Khargonekar Fadi J. Kurdahi MQ 25 11 0 11 Aug 2022
Generating and Detecting True Ambiguity: A Forgotten Danger in DNN Supervision Testing Michael Weiss A. Gómez Paolo Tonella AAML 18 6 0 21 Jul 2022
Guiding the retraining of convolutional neural networks against adversarial inputs Francisco Durán Silverio Martínez-Fernández Michael Felderer Xavier Franch AAML 38 1 0 08 Jul 2022
Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks Jiaxiang Liu Yunhan Xing Xiaomu Shi Fu Song Zhiwu Xu Zhong Ming 24 10 0 02 Jul 2022
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective Mark Huasong Meng Guangdong Bai Sin Gee Teo Zhe Hou Yan Xiao Yun Lin Jin Song Dong AAML 32 43 0 24 Jun 2022
A Search-Based Testing Approach for Deep Reinforcement Learning Agents Amirhossein Zolfagharian Manel Abdellatif Lionel C. Briand M. Bagherzadeh Ramesh S 45 27 0 15 Jun 2022
AEON: A Method for Automatic Evaluation of NLP Test Cases Jen-tse Huang Jianping Zhang Wenxuan Wang Pinjia He Yuxin Su Michael R. Lyu 40 23 0 13 May 2022
Search-Based Testing of Reinforcement Learning Martin Tappler Filip Cano Córdoba B. Aichernig Bettina Könighofer ELM OffRL 27 23 0 07 May 2022
Software Testing for Machine Learning D. Marijan A. Gotlieb AAML 22 27 0 30 Apr 2022
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System Markus Borg Jens Henriksson Kasper Socha Olof Lennartsson Elias Sonnsjo Lonegren T. Bui Piotr Tomaszewski S. Sathyamoorthy Sebastian Brink M. H. Moghadam 35 23 0 16 Apr 2022
Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment Qiang Hu Yuejun Guo Maxime Cordy Xiaofei Xie Wei Ma Mike Papadakis Yves Le Traon MQ 44 1 0 08 Apr 2022
LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing Qiang Hu Yuejun Guo Maxime Cordy Xiaofei Xie Mike Papadakis Yves Le Traon 23 5 0 08 Apr 2022
Testing Feedforward Neural Networks Training Programs Houssem Ben Braiek Foutse Khomh AAML 11 14 0 01 Apr 2022
Exploring ML testing in practice -- Lessons learned from an interactive rapid review with Axis Communications Qunying Song Markus Borg Emelie Engström H. Ardö Sergio Rico 14 10 0 30 Mar 2022
NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks Xiaofei Xie Tianlin Li Jian-Xun Wang Lei Ma Qing Guo Felix Juefei Xu Yang Liu AAML 21 51 0 24 Mar 2022
SoK: On the Semantic AI Security in Autonomous Driving Junjie Shen Ningfei Wang Ziwen Wan Yunpeng Luo Takami Sato ... Zhenyu Zhong Kang Li Ziming Zhao Chunming Qiao Qi Alfred Chen AAML 23 40 0 10 Mar 2022
MUC-driven Feature Importance Measurement and Adversarial Analysis for Random Forest Shucen Ma Jianqi Shi Yanhong Huang Shengchao Qin Zhe Hou AAML 24 4 0 25 Feb 2022
Testing Deep Learning Models: A First Comparative Study of Multiple Testing Techniques M. K. Ahuja A. Gotlieb Helge Spieker AAML 16 4 0 24 Feb 2022
Coverage-Guided Tensor Compiler Fuzzing with Joint IR-Pass Mutation Jiawei Liu Yuxiang Wei Sen Yang Yinlin Deng Lingming Zhang 33 41 0 21 Feb 2022
Excitement Surfeited Turns to Errors: Deep Learning Testing Framework Based on Excitable Neurons Haibo Jin Ruoxi Chen Haibin Zheng Jinyin Chen Yao Cheng Yue Yu Xianglong Liu AAML 28 6 0 12 Feb 2022
EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators Lois Orosa Skanda Koppula Yaman Umuroglu Konstantinos Kanellopoulos Juan Gómez Luna Michaela Blott K. Vissers O. Mutlu 46 4 0 04 Feb 2022
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems Andrea Stocco Brian Pulfer Paolo Tonella 27 68 0 21 Dec 2021