Primary Studies
This page lists the 125 primary studies included in the survey Fuzzing AI Systems: Foundations, Techniques, and Open Challenges.
The studies were identified within the January 2015–February 2026 search window. Each study retains its stable paper identifier (PID), which is used throughout the companion website to connect venue, technique, oracle, failure, and other study-level mappings.
Note: PID values are intentionally not renumbered after exclusions. Gaps in the sequence preserve traceability to the screening and annotation datasets.
How to Use This Catalogue
- Click a paper title or DOI to open the publication record.
- Links from the study-mapping tables point directly to the corresponding PID on this page.
- Use the browser’s search function to locate a PID, title, author, venue, or BibTeX key.
- Machine-readable metadata and detailed annotations are available in the replication package.
Primary-Study Catalogue
| PID | Study | Year | Venue | Publication Link |
|---|---|---|---|---|
| P001 |
NNsmith: Generating Diverse and Valid Test Cases for Deep Learning Compilers Liu, Jiawei; Lin, Jinkun; Ruffy, Fabian; Tan, Cheng; Li, Jinyang; Panda, Aurojit; Zhang, Lingming BibKey: liu2023nnsmith
|
2023 | ASPLOS Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 |
DOI10.1145/3575693.3575707 |
| P002 |
Your Fix Is My Exploit: Enabling Comprehensive DL Library API Fuzzing with Large Language Models Zhang, Kunpeng; Wang, Shuai; Han, Jitao; Zhu, Xiaogang; Li, Xian; Wang, Shaohua; Wen, Sheng BibKey: zhang_your_fix_2025
|
2025 | ICSE 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE) |
DOI10.1109/icse55347.2025.00041 |
| P003 |
TensorJSFuzz: Effective Testing of Web-Based Deep Learning Frameworks via Input-Constraint Extraction Quan, Lili; Xie, Xiaofei; Guo, Qianyu; Jiang, Lingxiao; Chen, Sen; Wang, Junjie; Li, Xiaohong BibKey: quan_tensorjsfuzz_2025
|
2025 | WWW Proceedings of the ACM on Web Conference 2025 |
DOI10.1145/3696410.3714649 |
| P004 |
DeepCNP: An Efficient White-Box Testing of Deep Neural Networks by Aligning Critical Neuron Paths Weiguang Liu; Senlin Luo; Limin Pan; Zhao Zhang BibKey: liu_deepcnp_2025
|
2025 | IST Information and Software Technology |
DOI10.1016/j.infsof.2024.107640 |
| P005 |
Towards More Complete Constraints for Deep Learning Library Testing via Complementary Set Guided Refinement Go, Gwihwan; Zhou, Chijin; Zhang, Quan; Zou, Xiazijian; Shi, Heyuan; Jiang, Yu BibKey: go_towards_2024
|
2024 | ISSTA Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3650212.3680364 |
| P006 |
NeuRI: Diversifying DNN Generation via Inductive Rule Inference Liu, Jiawei; Peng, Jinjun; Wang, Yuyao; Zhang, Lingming BibKey: liu_neuri_2023
|
2023 | FSE Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
DOI10.1145/3611643.3616337 |
| P007 |
DLRegion: Coverage-Guided Fuzz Testing of Deep Neural Networks with Region-Based Neuron Selection Strategies Chuanqi Tao; Yali Tao; Hongjing Guo; Zhiqiu Huang; Xiaobing Sun BibKey: tao_dlregion_2023
|
2023 | IST Information and Software Technology |
DOI10.1016/j.infsof.2023.107266 |
| P008 |
Fuzzing Deep-Learning Libraries via Automated Relational API Inference Deng, Yinlin; Yang, Chenyuan; Wei, Anjiang; Zhang, Lingming BibKey: deng_fuzzing_2022
|
2022 | FSE Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
DOI10.1145/3540250.3549085 |
| P009 |
Muffin: Testing Deep Learning Libraries via Neural Architecture Fuzzing Gu, Jiazhen; Luo, Xuchuan; Zhou, Yangfan; Wang, Xin BibKey: gu_muffin_2022
|
2022 | ICSE Proceedings of the 44th International Conference on Software Engineering |
DOI10.1145/3510003.3510092 |
| P010 |
Free Lunch for Testing: Fuzzing Deep-Learning Libraries from Open Source Wei, Anjiang; Deng, Yinlin; Yang, Chenyuan; Zhang, Lingming BibKey: wei2022freefuzz
|
2022 | ICSE Proceedings of the 44th International Conference on Software Engineering |
DOI10.1145/3510003.3510041 |
| P011 |
Ache-Fuzz: Constraint-Aware Fuzzing for Vulnerability Discovery in Distributed Deep Learning Frameworks Zhao Zhang; Senlin Luo; Liyuan Liu; Limin Pan BibKey: zhang_ache-fuzz_2026
|
2026 | JSS Journal of Systems and Software |
DOI10.1016/j.jss.2026.112796 |
| P012 |
CtrlFuzz: A Controllable Diffusion-Based Fuzz Testing for Deep Neural Networks via Coverage-Aware Manifold Guidance Aoshuang Ye; Shilin Zhang; Runze Yan; Jianpeng Ke; Fei Zhu; Benxiao Tang BibKey: ye_ctrlfuzz_2025
|
2025 | IST Information and Software Technology |
DOI10.1016/j.infsof.2025.107856 |
| P013 |
Large Language Models Are Edge-Case Generators: Crafting Unusual Programs for Fuzzing Deep Learning Libraries Deng, Yinlin; Xia, Chunqiu Steven; Yang, Chenyuan; Zhang, Shizhuo Dylan; Yang, Shujing; Zhang, Lingming BibKey: deng_large_2024
|
2024 | ICSE Proceedings of the IEEE/ACM 46th International Conference on Software Engineering |
DOI10.1145/3597503.3623343 |
| P014 |
Mutation-Based Deep Learning Framework Testing Method in JavaScript Environment Zou, Yinglong; Zhai, Juan; Fang, Chunrong; Liu, Jiawei; Zheng, Tao; Chen, Zhenyu BibKey: zou_mutation-based_2024
|
2024 | ASE Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering |
DOI10.1145/3691620.3695478 |
| P015 |
Large Language Models Are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models Deng, Yinlin; Xia, Chunqiu Steven; Peng, Haoran; Yang, Chenyuan; Zhang, Lingming BibKey: deng_large_2023
|
2023 | ISSTA Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3597926.3598067 |
| P016 |
Fuzzing Automatic Differentiation in Deep-Learning Libraries Yang, Chenyuan; Deng, Yinlin; Yao, Jiayi; Tu, Yuxing; Li, Hanchi; Zhang, Lingming BibKey: yang_fuzzing_2023
|
2023 | ICSE 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) |
DOI10.1109/icse48619.2023.00105 |
| P017 |
DocTer: Documentation-Guided Fuzzing for Testing Deep Learning API Functions Xie, Danning; Li, Yitong; Kim, Mijung; Pham, Hung Viet; Tan, Lin; Zhang, Xiangyu; Godfrey, Michael W. BibKey: xie2022docter
|
2022 | ISSTA Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3533767.3534220 |
| P018 |
HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing Ma, Dongning; Guo, Jianmin; Jiang, Yu; Jiao, Xun BibKey: ma_hdtest_2021
|
2022 | DAC 2021 58th ACM/IEEE Design Automation Conference (DAC) |
DOI10.1109/dac18074.2021.9586169 |
| P019 |
MDPFuzz: Testing Models Solving Markov Decision Processes Pang, Qi; Yuan, Yuanyuan; Wang, Shuai BibKey: pang2022mdpfuzz
|
2022 | ISSTA Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3533767.3534388 |
| P020 |
ExAIS: Executable AI Semantics Schumi, Richard; Sun, Jun BibKey: schumi_exais_2022
|
2022 | ICSE Proceedings of the 44th International Conference on Software Engineering |
DOI10.1145/3510003.3510112 |
| P021 |
Predoo: Precision Testing of Deep Learning Operators Zhang, Xufan; Sun, Ning; Fang, Chunrong; Liu, Jiawei; Liu, Jia; Chai, Dong; Wang, Jiang; Chen, Zhenyu BibKey: zhang_predoo_2021
|
2021 | ISSTA Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3460319.3464843 |
| P022 |
DeFinder: Error-Sensitive Testing of Deep Neural Networks via Vulnerability Interpretation Aoshuang Ye; Shilin Zhang; Benxiao Tang; Jianpeng Ke; Yiru Zhao; Tao Peng BibKey: ye_definder_2025
|
2025 | JNCA Journal of Network and Computer Applications |
DOI10.1016/j.jnca.2025.104212 |
| P023 |
Large Language Models Can Connect the Dots: Exploring Model Optimization Bugs with Domain Knowledge-Aware Prompts Guan, Hao; Bai, Guangdong; Liu, Yepang BibKey: guan_large_2024
|
2024 | ISSTA Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3650212.3680383 |
| P024 |
Fuzzing for Deep Learning Models Wu, Bo; Chen, Deng BibKey: wu_fuzzing_2023
|
2024 | ICRSA Proceedings of the 2023 6th International Conference on Robot Systems and Applications |
DOI10.1145/3655532.3655574 |
| P025 |
Semantic Data Augmentation for Deep Learning Testing Using Generative AI Missaoui, Sondess; Gerasimou, Simos; Matragkas, Nicholas BibKey: missaoui_semantic_2023
|
2024 | ASE 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) |
DOI10.1109/ase56229.2023.00194 |
| P026 |
Dance of the ADS: Orchestrating Failures through Historically-Informed Scenario Fuzzing Wang, Tong; Gu, Taotao; Deng, Huan; Li, Hu; Kuang, Xiaohui; Zhao, Gang BibKey: wang_dance_2024
|
2024 | ISSTA Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3650212.3680344 |
| P027 |
CriticalFuzz: A Critical Neuron Coverage-Guided Fuzz Testing Framework for Deep Neural Networks Tongtong Bai; Song Huang; Yifan Huang; Xingya Wang; Chunyan Xia; Yubin Qu; Zhen Yang BibKey: bai_criticalfuzz_2024
|
2024 | IST Information and Software Technology |
DOI10.1016/j.infsof.2024.107476 |
| P028 |
Fuzzing Deep Learning Compilers with HIRGEN Ma, Haoyang; Shen, Qingchao; Tian, Yongqiang; Chen, Junjie; Cheung, Shing-Chi BibKey: ma_fuzzing_2023
|
2023 | ISSTA Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3597926.3598053 |
| P029 |
Graph-Based Fuzz Testing for Deep Learning Inference Engines Luo, Weisi; Chai, Dong; Run, Xiaoyue; Wang, Jiang; Fang, Chunrong; Chen, Zhenyu BibKey: luo_graph-based_2021
|
2021 | ICSE 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) |
DOI10.1109/icse43902.2021.00037 |
| P030 |
RobOT: Robustness-Oriented Testing for Deep Learning Systems Wang, Jingyi; Chen, Jialuo; Sun, Youcheng; Ma, Xingjun; Wang, Dongxia; Sun, Jun; Cheng, Peng BibKey: wang_robot_2021
|
2021 | ICSE 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) |
DOI10.1109/icse43902.2021.00038 |
| P031 |
Coverage-Guided Fuzzing for Feedforward Neural Networks Xie, Xiaofei; Chen, Hongxu; Li, Yi; Ma, Lei; Liu, Yang; Zhao, Jianjun BibKey: xie_coverage-guided_2019
|
2020 | ASE 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE) |
DOI10.1109/ase.2019.00127 |
| P032 |
DeepHunter: A Coverage-Guided Fuzz Testing Framework for Deep Neural Networks Xie, Xiaofei; Ma, Lei; Juefei-Xu, Felix; Xue, Minhui; Chen, Hongxu; Liu, Yang; Zhao, Jianjun; Li, Bo; Yin, Jianxiong; See, Simon BibKey: xie2019deephunter
|
2019 | ISSTA Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3293882.3330579 |
| P033 |
DeepStellar: Model-Based Quantitative Analysis of Stateful Deep Learning Systems Du, Xiaoning; Xie, Xiaofei; Li, Yi; Ma, Lei; Liu, Yang; Zhao, Jianjun BibKey: du_deepstellar_2019
|
2019 | FSE Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
DOI10.1145/3338906.3338954 |
| P034 |
Fuzzing MLIR Compilers with Custom Mutation Synthesis Limpanukorn, Ben; Wang, Jiyuan; Kang, Hong Jin; Zhou, Zitong; Kim, Miryung BibKey: limpanukorn_fuzzing_2025
|
2025 | ICSE 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE) |
DOI10.1109/icse55347.2025.00037 |
| P035 |
Curiosity-Driven Testing for Sequential Decision-Making Process He, Junda; Yang, Zhou; Shi, Jieke; Yang, Chengran; Kim, Kisub; Xu, Bowen; Zhou, Xin; Lo, David BibKey: he_curiosity-driven_2024
|
2024 | ICSE Proceedings of the IEEE/ACM 46th International Conference on Software Engineering |
DOI10.1145/3597503.3639149 |
| P036 |
MLIR-Smith: Random Program Generation for Fuzzing MLIR Compiler Infrastructure Wang, Haoyu; Chen, Junjie; Xie, Chuyue; Liu, Shuang; Wang, Zan; Shen, Qingchao; Zhao, Yingquan BibKey: zhang2023mlirsmith
|
2024 | ASE 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) |
DOI10.1109/ase56229.2023.00120 |
| P038 |
Regression Fuzzing for Deep Learning Systems You, Hanmo; Wang, Zan; Chen, Junjie; Liu, Shuang; Li, Shuochuan BibKey: you_regression_2023
|
2023 | ICSE 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) |
DOI10.1109/icse48619.2023.00019 |
| P039 |
QATest: A Uniform Fuzzing Framework for Question Answering Systems Liu, Zixi; Feng, Yang; Yin, Yining; Sun, Jingyu; Chen, Zhenyu; Xu, Baowen BibKey: liu_qatest_2022
|
2023 | ASE Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering |
DOI10.1145/3551349.3556929 |
| P040 |
GradFuzz: Fuzzing Deep Neural Networks with Gradient Vector Coverage for Adversarial Examples Leo Hyun Park; Soochang Chung; Jaeuk Kim; Taekyoung Kwon BibKey: park_gradfuzz_2023
|
2023 | Neurocomputing | DOI10.1016/j.neucom.2022.12.019 |
| P041 |
Metamorphic Relations via Relaxations: An Approach to Obtain Oracles for Action-Policy Testing Eniser, Hasan Ferit; Gros, Timo P.; Wüstholz, Valentin; Hoffmann, Jörg; Christakis, Maria BibKey: eniser_metamorphic_2022
|
2022 | ISSTA Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3533767.3534392 |
| P042 |
DLFuzz: Differential Fuzzing Testing of Deep Learning Systems Guo, Jianmin; Jiang, Yu; Zhao, Yue; Chen, Quan; Sun, Jiaguang BibKey: guo_dlfuzz_2018
|
2018 | FSE Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
DOI10.1145/3236024.3264835 |
| P043 |
Brittle Features of Device Authentication Garcia, Washington; Chhotaray, Animesh; Choi, Joseph I.; Adari, Suman Kalyan; Butler, Kevin R.B.; Jha, Somesh BibKey: garcia_brittle_2021
|
2021 | CODASPY Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy |
DOI10.1145/3422337.3447842 |
| P044 |
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks Zhang, Fuyuan; Chowdhury, Sankalan Pal; Christakis, Maria BibKey: zhang_deepsearch_2020
|
2020 | FSE Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
DOI10.1145/3368089.3409750 |
| P045 |
Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries Tizpaz-Niari, Saeid; Černý, Pavol; Trivedi, Ashutosh BibKey: tizpaz-niari_detecting_2020
|
2020 | ISSTA Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis |
DOI10.1145/3395363.3404540 |
| P046 |
Coverage-Guided Tensor Compiler Fuzzing with Joint IR-Pass Mutation Jiawei Liu, Yuxiang Wei, Sen Yang, Yinlin Deng, Lingming Zhang BibKey: liu2022tzer
|
2022 | OOPSLA Proc. ACM Program. Lang. |
DOI10.1145/3527317 |
| P049 |
DeepRoad: GAN-Based Metamorphic Testing and Input Validation Framework for Autonomous Driving Systems Mengshi Zhang, Yuqun Zhang, Lingming Zhang, Cong Liu, S. Khurshid BibKey: zhang2018deeproad
|
2018 | ASE International Conference on Automated Software Engineering |
DOI10.1145/3238147.3238187 |
| P050 |
MODE: Automated Neural Network Model Debugging via State Differential Analysis and Input Selection Shiqing Ma, Yingqi Liu, Wen-Chuan Lee, X. Zhang, A. Grama BibKey: ma_mode_2018
|
2018 | FSE ESEC/SIGSOFT FSE |
DOI10.1145/3236024.3236082 |
| P051 |
DeepMutation: Mutation Testing of Deep Learning Systems L. Ma, Fuyuan Zhang, Jiyuan Sun, Minhui Xue, Bo Li, Felix Juefei-Xu, Chao Xie, Li Li, Yang Liu, Jianjun Zhao, Yadong Wang BibKey: ma_deepmutation_2018
|
2018 | ISSRE IEEE International Symposium on Software Reliability Engineering |
DOI10.1109/ISSRE.2018.00021 |
| P058 |
Fuzz Testing Based Data Augmentation to Improve Robustness of Deep Neural Networks Xiang Gao, Ripon K. Saha, M. Prasad, Abhik Roychoudhury BibKey: gao_fuzz_2020
|
2020 | ICSE International Conference on Software Engineering |
DOI10.1145/3377811.3380415 |
| P060 |
DeepMutation++: A Mutation Testing Framework for Deep Learning Systems Q. Hu, L. Ma, Xiaofei Xie, Bing Yu, Yang Liu, Jianjun Zhao BibKey: hu_deepmutation_2019
|
2019 | ASE International Conference on Automated Software Engineering |
DOI10.1109/ASE.2019.00126 |
| P061 |
Provably Valid and Diverse Mutations of Real-World Media Data for DNN Testing Yuanyuan Yuan, Qi Pang, Shuai Wang BibKey: yuan_provably_2024
|
2021 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2024.3370807 |
| P066 |
DriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing Seulbae Kim, Major Liu, J. Rhee, Yuseok Jeon, Yonghwi Kwon, C. Kim BibKey: kim2022drivefuzz
|
2022 | CCS Conference on Computer and Communications Security |
DOI10.1145/3548606.3560558 |
| P068 |
Neural Network Guided Evolutionary Fuzzing for Finding Traffic Violations of Autonomous Vehicles Ziyuan Zhong, Gail E Kaiser, Baishakhi Ray BibKey: zhong_neural_2023
|
2021 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2022.3195640 |
| P069 |
AV-FUZZER: Finding Safety Violations in Autonomous Driving Systems Guanpeng Li, Yiran Li, Saurabh Jha, Timothy Tsai, Michael B. Sullivan, S. Hari, Z. Kalbarczyk, R. Iyer BibKey: li2020avfuzzer
|
2020 | ISSRE IEEE International Symposium on Software Reliability Engineering |
DOI10.1109/ISSRE5003.2020.00012 |
| P076 |
BCI-Fuzz: Bug-Triggering Code Innovated to Fuzz Deep Learning Libraries Zhiyang Zhao, Limin Pan, Siyuan Shao, Senlin Luo BibKey: zhao_bci-fuzz_2026
|
2026 | JSS Journal of Systems and Software |
DOI10.1016/j.jss.2026.112822 |
| P077 |
Optimization-Aware Test Generation for Deep Learning Compilers Qingchao Shen, Zan Wang, Haoyang Ma, Yongqiang Tian, Lili Huang, Zibo Xiao, Junjie Chen, Shing-Chi Cheung BibKey: shen_optimization-aware_2025
|
2025 | arXiv arXiv.org |
DOI10.48550/arXiv.2511.18918 |
| P078 |
MirrorFuzz: Leveraging LLM and Shared Bugs for Deep Learning Framework APIs Fuzzing Shiwen Ou, Yuwei Li, Lu Yu, Chengkun Wei, Tingke Wen, Qiangpu Chen, Yu Chen, Haizhi Tang, Zulie Pan BibKey: ou_mirrorfuzz_2025
|
2025 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2025.3619966 |
| P079 |
Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR Zeyu Sun, Jingjing Liang, Weiyi Wang, Chenyao Suo, Junjie Chen, Fanjiang Xu BibKey: sun_interleaved_2025
|
2025 | ASE International Conference on Automated Software Engineering |
DOI10.1109/ASE63991.2025.00196 |
| P080 |
Evaluating the Effectiveness of Coverage-Guided Fuzzing for Testing Deep Learning Library APIs Feiran Qin, M. M. A. Naziri, Hengyu Ai, Saikat Dutta, Marcelo d’Amorim BibKey: qin_evaluating_2025
|
2025 | arXiv arXiv.org |
DOI10.48550/arXiv.2509.14626 |
| P081 |
NÜWA: Enhancing MLIR Fuzzing with LLM-Driven Generation and Adaptive Mutation Bocan Cao, Weiyuan Tong, Zhanyong Tang, Zixu Wang, Hao Huang, Yuheng Yan BibKey: cao_nuwa_2025
|
2025 | ICSME IEEE International Conference on Software Maintenance and Evolution |
DOI10.1109/ICSME64153.2025.00055 |
| P082 |
May the Feedback Be with You! Unlocking the Power of Feedback-Driven Deep Learning Framework Fuzzing via LLMs Shaoyu Yang, Chunrong Fang, Haifeng Lin, Xiang Chen, Zhenyu Chen BibKey: yang_may_2025
|
2025 | arXiv arXiv.org |
DOI10.48550/arXiv.2506.17642 |
| P083 |
Directed Testing in MLIR: Unleashing Its Potential by Overcoming the Limitations of Random Fuzzing Weiyuan Tong, Zixu Wang, Zhanyong Tang, Jianbin Fang, Yuqun Zhang, Guixin Ye BibKey: tong_directed_2025
|
2025 | PACMSE Proc. ACM Softw. Eng. |
DOI10.1145/3729372 |
| P086 |
Scuzer: A Scheduling Optimization Fuzzer for TVM Xiangxiang Chen, Xingwei Lin, Jingyi Wang, Jun Sun, Jiashui Wang, Wenhai Wang BibKey: chen_s_2025
|
2024 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3705308 |
| P087 |
History-Driven Fuzzing for Deep Learning Libraries Nima Shiri Harzevili, Mohammad Mahdi Mohajer, Moshi Wei, Hung Viet Pham, Song Wang BibKey: shiri_harzevili_history-driven_2025
|
2024 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3688838 |
| P088 |
MoCo: Fuzzing Deep Learning Libraries via Assembling Code Pin Ji, Yang Feng, Duo Wu, Lin Yan, Peng Chen, Jia Liu, Zhihong Zhao BibKey: ji_moco_2025
|
2024 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2024.3509975 |
| P089 |
TorchProbe: Fuzzing Dynamic Deep Learning Compilers Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si BibKey: hur_torchprobe_2023
|
2023 | APLAS Asian Symposium on Programming Languages and Systems |
DOI10.48550/arXiv.2310.20078 |
| P090 |
WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models Chenyuan Yang, Yinlin Deng, Runyu Lu, Jiayi Yao, Jiawei Liu, Reyhaneh Jabbarvand, Lingming Zhang BibKey: yang_whitefox_2024
|
2023 | OOPSLA Proc. ACM Program. Lang. |
DOI10.1145/3689736 |
| P091 |
DeepDiffer: Find Deep Learning Compiler Bugs via Priority-Guided Differential Fuzzing Kuiliang Lin, Xiangpu Song, Yingpei Zeng, Shanqing Guo BibKey: lin_deepdiffer_2023
|
2023 | QRS International Conference on Software Quality, Reliability and Security |
DOI10.1109/QRS60937.2023.00066 |
| P095 |
D3: Differential Testing of Distributed Deep Learning with Model Generation Jiannan Wang, Hung Viet Pham, Qi Li, Lin Tan, Yu Guo, Adnan Aziz, Erik Meijer BibKey: wang_d3_2025
|
2025 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2024.3461657 |
| P096 |
CGFuzz: A Dynamic Test Case Generation Method for DL Framework Based on Function Coverage Qing Cai, Beibei Yin, Jing-Ao Shi BibKey: cai_cgfuzz_2024
|
2024 | QRS Companion IEEE International Conference on Software Quality, Reliability and Security Companion |
DOI10.1109/QRS-C63300.2024.00070 |
| P099 |
LLM-Powered Silent Bug Fuzzing in Deep Learning Libraries via Versatile and Controlled Bug Transfer Kunpeng Zhang, Dongwei Xiao, Daoyuan Wu, Shuai Wang, Jiali Zhao, Yuanyi Lin, Tongtong Xu, Shaohua Wang BibKey: zhang_llm-powered_2026
|
2026 | OOPSLA Proceedings of the ACM on Programming Languages (OOPSLA1) |
DOI10.1145/3798258 |
| P100 |
Testing Deep Learning Libraries via Neurosymbolic Constraint Learning Abid Naziri, Shinhae Kim, Alex Qin, Marcelo d’Amorim, Saikat Dutta BibKey: naziri_testing_2026
|
2026 | arXiv arXiv.org |
DOI10.48550/arXiv.2601.15493 |
| P101 |
Automating Fuzz Driver Generation for Deep Learning Libraries with Large Language Models Tianming Zheng, Fanchao Meng, Ping Yi, Yue Wu BibKey: zheng_automating_2026
|
2026 | Cybersecurity | DOI10.1186/s42400-025-00532-9 |
| P103 |
A Multi-Agent Fuzzing Framework for Deep Learning Library Rongtao Liao, Shiwen Ou, Xuehu Yan, Kailong Zhu BibKey: liao_multi-agent_2025
|
2025 | SMC IEEE International Conference on Systems, Man and Cybernetics |
DOI10.1109/SMC58881.2025.11343067 |
| P104 |
Enhancing Test Case Generation for Fuzzing Deep Learning Libraries Using Few-Shot Learning Bing Yang, Senyi Li, Junqiang Li, Kaiyu Du, Hongfang Yu, Jian Sun, Long Luo BibKey: yang_enhancing_2025
|
2025 | DSC International Conference on Data Science in Cyberspace |
DOI10.1109/DSC67331.2025.00089 |
| P106 |
FuMi: A Runtime Fuzz-Based Machine Learning Precision Measurement and Testing Framework Peng Zhang, Mike Papadakis, Yuming Zhou BibKey: zhang_fumi_2026
|
2025 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3734866 |
| P111 |
ConFL: Constraint-Guided Fuzzing for Machine Learning Framework Zhao Liu, Quanchen Zou, Tianyu Yu, Xuan Wang, Guozhu Meng, Kai Chen, Deyue Zhang BibKey: liu_confl_2023
|
2023 | arXiv arXiv.org |
DOI10.48550/arXiv.2307.05642 |
| P113 |
ACETest: Automated Constraint Extraction for Testing Deep Learning Operators Jingyi Shi, Yang Xiao, Yuekang Li, Yeting Li, Dongsong Yu, Chendong Yu, Hui Su, Yufeng Chen, Wei Huo BibKey: shen2024acetest
|
2023 | ISSTA International Symposium on Software Testing and Analysis |
DOI10.1145/3597926.3598088 |
| P114 |
SKIPFUZZ: Active Learning-Based Input Selection for Fuzzing Deep Learning Libraries Hong Jin Kang, Pattarakrit Rattanukul, S. A. Haryono, Truong-Giang Nguyen, Chaiyong Ragkhitwetsagul, C. Păsăreanu, David Lo BibKey: kang_skipfuzz_2022
|
2022 | arXiv arXiv.org |
DOI10.48550/arXiv.2212.04038 |
| P116 |
DKFuzz: An Automated Approach for Testing the Underlying Kernels of Deep Learning Frameworks Hanqing Li, Xiang Li, Yuanping Nie, Suiyuan Du, Qiong Wu BibKey: li_dkfuzz_2025
|
2025 | ASENS 2025 2nd International Conference on Algorithms, Software Engineering and Network Security (ASENS) |
DOI10.1109/ASENS64990.2025.11011223 |
| P119 |
Generation-Based Differential Fuzzing for Deep Learning Libraries Jiawei Liu, Yuheng Huang, Zhijie Wang, Lei Ma, Chunrong Fang, Mingzheng Gu, Xufan Zhang, Zhenyu Chen BibKey: liu_generation-based_2024
|
2023 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3628159 |
| P120 |
COMET: Coverage-Guided Model Generation for Deep Learning Library Testing Meiziniu Li, Jialun Cao, Yongqiang Tian, T. Li, Ming Wen, S. Cheung BibKey: li_comet_2023
|
2022 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3583566 |
| P121 |
Python Fuzzing for Trustworthy Machine Learning Frameworks Ilya Yegorov, Eli Kobrin, Darya Parygina, A. Vishnyakov, A. Fedotov BibKey: yegorov_python_2024
|
2024 | JMS Journal of Mathematical Sciences |
DOI10.1007/s10958-024-07424-2 |
| P122 |
HFUZZER: Testing Large Language Models for Package Hallucinations via Phrase-Based Fuzzing Yukai Zhao, Menghan Wu, Xing Hu, Xin Xia BibKey: zhao_hfuzzer_2025
|
2025 | ASE International Conference on Automated Software Engineering |
DOI10.1109/ASE63991.2025.00225 |
| P125 |
Towards Adaptive Multi-Object Fuzzing: A Map-Aware Reinforcement Approach for Autonomous Driving Systems Qi Jin, Tingting Wu, Zuohua Ding, Yongkui Xu, Yunwei Dong BibKey: jin_towards_2025
|
2025 | ICPADS International Conference on Parallel and Distributed Systems |
DOI10.1109/ICPADS67057.2025.11322949 |
| P127 |
ScenarioFuzz-LLM: Enhancing Diversity in Autonomous Driving Scenario Fuzzing with LLMs Shenghao Lin, Fansong Chen, Laile Xi, Kaiyu Xie, Yaowen Zheng, Haiqiang Fei, Yuyan Sun, Hongsong Zhu BibKey: lin_scenariofuzz-llm_2025
|
2025 | CSCWD International Conference on Computer Supported Cooperative Work in Design |
DOI10.1109/CSCWD64889.2025.11033362 |
| P130 |
ReinSeed: Reinforcement Fuzz Testing with Multiphase Seed Optimization for Autonomous Driving Systems Qi Jin, Tingting Wu, Yunwei Dong, Zuohua Ding, Yongkui Xu BibKey: jin_reinseed_2025
|
2025 | IET Software IET (Institution of Engineering and Technology) Software |
DOI10.1049/sfw2/8657455 |
| P133 |
Fuzzing with Sequence Diversity Inference for Sequential Decision-Making Model Testing Kairui Wang, Yawen Wang, Junjie Wang, Qing Wang BibKey: wang_fuzzing_2023
|
2023 | ISSRE IEEE International Symposium on Software Reliability Engineering |
DOI10.1109/ISSRE59848.2023.00041 |
| P136 |
RGChaser: A RL-Guided Fuzz and Mutation Testing Framework for Deep Learning Systems Yuteng Lu, Kaicheng Shao, Weidi Sun, Meng Sun BibKey: lu_rgchaser_2022
|
2022 | DSA International Conferences on Dependable Systems and Their Applications |
DOI10.1109/DSA56465.2022.00012 |
| P137 |
TAEFuzz: Automatic Fuzzing for Image-Based Deep Learning Systems via Transferable Adversarial Examples Shunhui Ji, Changrong Huang, Bin Ren, Hai Dong, Lars Grunske, Yan Xiao, Pengcheng Zhang BibKey: ji_taefuzz_2025
|
2025 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3714463 |
| P140 |
MalFuzz: Coverage-Guided Fuzzing on Deep Learning-Based Malware Classification Model Yuying Liu, Pin Yang, Peng Jia, Ziheng He, Hairu Luo BibKey: yang2022malfuzz
|
2022 | PLOS ONE | DOI10.1371/journal.pone.0273804 |
| P142 |
DFuzzer: Diversity-Driven Seed Queue Construction of Fuzzing for Deep Learning Models Hepeng Dai, Chang-ai Sun, Huai Liu, Xiangyu Zhang BibKey: dai_dfuzzer_2024
|
2024 | TR IEEE Transactions on Reliability |
DOI10.1109/TR.2023.3322406 |
| P143 |
CAGFuzz: Coverage-Guided Adversarial Generative Fuzzing Testing for Image-Based Deep Learning Systems Pengcheng Zhang, Bin Ren, Hai Dong, Qiyin Dai BibKey: zhang_cagfuzz_2022
|
2022 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2021.3124006 |
| P144 |
Spatial Semantic Fuzzing for LiDAR-Based Autonomous Driving Perception Systems An Guo, Zhiwei Su, Xinyu Gao, Chunrong Fang, Senrong Wang, Haoxiang Tian, Wu Wen, Lei Ma, Zhenyu Chen BibKey: guo_spatial_2026
|
2026 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2025.3627580 |
| P145 |
GMFuzz: Integrating Hierarchical Mutation and Fidelity Constraints for Coverage-Guided DNN Security Testing Yue Cui, Guangshun Li, Kexin Yang, Junhua Wu BibKey: cui_gmfuzz_2025
|
2025 | TrustCom International Conference on Trust, Security and Privacy in Computing and Communications |
DOI10.1109/Trustcom66490.2025.00246 |
| P146 |
Deep2Fuzz: Coverage-Guided Reinforcement Fuzzing towards Deep Neural Networks Weiguo Lin, Yaxuan Xie, Ruitong Liu, Zexu Dang, Jinyi Hao, Teng Li, Zhuoru Ma, Jianfeng Ma BibKey: lin_deep2fuzz_2025
|
2025 | NaNA International Conference on Networking and Network Applications |
DOI10.1109/NaNA66698.2025.00048 |
| P147 |
Adversarial Generation of Deep Neural Network Image Test Cases Based on Multi-Conditional Constraints Qingxia Yu, Chuanqi Tao BibKey: yu_adversarial_2025
|
2025 | QRS International Conference on Software Quality, Reliability and Security |
DOI10.1109/QRS65678.2025.00042 |
| P148 |
Coverage-Guided Many-Objective Test Generation for Deep Neural Networks Dongcheng Li, W. E. Wong, Hu Liu, Man Zhao, Zizhao Chen BibKey: li_coverage-guided_2025
|
2025 | QRS Companion IEEE International Conference on Software Quality, Reliability and Security Companion |
DOI10.1109/QRS-C65679.2025.00096 |
| P152 |
XMutant: XAI-Based Fuzzing for Deep Learning Systems Xingcheng Chen, Matteo Biagiola, Vincenzo Riccio, Marcelo d’Amorim, Andrea Stocco BibKey: chen_xmutant_2025
|
2025 | arXiv arXiv.org |
DOI10.48550/arXiv.2503.07222 |
| P153 |
A DNN Fuzz Testing Method Based on Gradient-Weighted Class Activation Map Zhouning Chen, Qiaoyun Liu, Shengxin Dai, Qiuhui Yang BibKey: chen_dnn_2024
|
2024 | APSEC Asia-Pacific Software Engineering Conference |
DOI10.1109/APSEC65559.2024.00011 |
| P154 |
Many-Objective Search-Based Coverage-Guided Automatic Test Generation for Deep Neural Networks Dongcheng Li, W. E. Wong, Hu Liu, Man Zhao BibKey: li_many-objective_2024
|
2024 | arXiv arXiv.org |
DOI10.48550/arXiv.2411.01033 |
| P156 |
DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks for Image Analysis Zohreh Aghababaeyan, Manel Abdellatif, Lionel Briand, Ramesh S. BibKey: aghababaeyan_diffgan_2025
|
2024 | TSE IEEE Transactions on Software Engineering |
DOI10.1109/TSE.2025.3611329 |
| P157 |
Neuron Semantic-Guided Test Generation for Deep Neural Networks Fuzzing Li Huang, Weifeng Sun, Meng Yan, Zhongxin Liu, Yan Lei, David Lo BibKey: huang_neuron_2025
|
2024 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3688835 |
| P158 |
Robust Black-Box Testing of Deep Neural Networks Using Co-Domain Coverage Aishwarya Gupta, Indranil Saha, Piyush Rai BibKey: gupta_robust_2024
|
2024 | arXiv arXiv.org |
DOI10.48550/arXiv.2408.06766 |
| P160 |
Context-Aware Fuzzing for Robustness Enhancement of Deep Learning Models Haipeng Wang, Zhengyuan Wei, Qili Zhou, W. Chan BibKey: wang_context-aware_2025
|
2024 | TOSEM ACM Transactions on Software Engineering and Methodology |
DOI10.1145/3680464 |
| P162 |
An Uncovered Neurons Information-Based Fuzzing Method for DNN Kecheng Tang, Jiantao Zhou, Xu Guo BibKey: tang_uncovered_2024
|
2024 | CSCWD International Conference on Computer Supported Cooperative Work in Design |
DOI10.1109/CSCWD61410.2024.10580820 |
| P164 |
Learning and Repair of Deep Reinforcement Learning Policies from Fuzz-Testing Data Martin Tappler, Andrea Pferscher, B. Aichernig, Bettina Könighofer BibKey: tappler_learning_2024
|
2024 | ICSE International Conference on Software Engineering |
DOI10.1145/3597503.3623311 |
| P165 |
Coverage-Guided Fuzzing for Deep Reinforcement Learning Systems Xiaohui Wan, Tiancheng Li, Weibin Lin, Yi Cai, Zheng Zheng BibKey: wan_coverage-guided_2024
|
2024 | JSS Journal of Systems and Software |
DOI10.1016/j.jss.2024.111963 |
| P167 |
DeepHC: Efficient Generating Tests with High Coverage for Deep Neural Networks Ju Teng, Tingting Yu, Rui Chen, Dongdong Gao, Chunpeng Jia BibKey: teng_deephc_2023
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2023 | QRS Companion IEEE International Conference on Software Quality, Reliability and Security Companion |
DOI10.1109/QRS-C60940.2023.00030 |
| P169 |
DeepAtash: Focused Test Generation for Deep Learning Systems Tahereh Zohdinasab, Vincenzo Riccio, P. Tonella BibKey: zohdinasab_deepatash_2023
|
2023 | ISSTA International Symposium on Software Testing and Analysis |
DOI10.1145/3597926.3598109 |
| P170 |
ASDF: A Differential Testing Framework for Automatic Speech Recognition Systems D. Yuen, A. Pang, Zhou Yang, Chun Yong Chong, M. Lim, David Lo BibKey: yuen_asdf_2023
|
2023 | ICIST International Conference on Information Control Systems & Technologies |
DOI10.1109/ICST57152.2023.00050 |
| P172 |
Mixed and Constrained Input Mutation for Effective Fuzzing of Deep Learning Systems L. Park, Jaeuk Kim, Jaewoo Park, T.-H. Kwon BibKey: park_mixed_2022
|
2022 | Information Sciences | DOI10.1016/j.ins.2022.10.079 |
| P174 |
Ex2: Monte Carlo Tree Search‐Based Test Inputs Prioritization for Fuzzing Deep Neural Networks Aoshuang Ye, Lina Wang, Lei Zhao, Jianpeng Ke BibKey: ye_ex2_2022
|
2022 | IJIS International Journal of Intelligent Systems |
DOI10.1002/int.23072 |
| P176 |
A White-Box Testing for Deep Neural Networks Based on Neuron Coverage Jing Yu, Shukai Duan, Xiaojun Ye BibKey: yu_white-box_2023
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2022 | TNNLS IEEE Transactions on Neural Networks and Learning Systems |
DOI10.1109/TNNLS.2022.3156620 |
| P178 |
DEEPMETIS: Augmenting a Deep Learning Test Set to Increase Its Mutation Score Vincenzo Riccio, Nargiz Humbatova, Gunel Jahangirova, P. Tonella BibKey: riccio_deepmetis_2021
|
2021 | ASE International Conference on Automated Software Engineering |
DOI10.1109/ASE51524.2021.9678764 |
| P180 |
CoCoFuzzing: Testing Neural Code Models with Coverage-Guided Fuzzing Moshi Wei, Yuchao Huang, Jinqiu Yang, Junjie Wang, Song Wang BibKey: wei_cocofuzzing_2021
|
2021 | TR IEEE Transactions on Reliability |
DOI10.1109/TR.2022.3208239 |
| P182 |
DeepCon: Contribution Coverage Testing for Deep Learning Systems Zhiyang Zhou, Wensheng Dou, Jie Liu, Chenxin Zhang, Jun Wei, Dan Ye BibKey: zhou_deepcon_2021
|
2021 | SANER IEEE International Conference on Software Analysis, Evolution, and Reengineering |
DOI10.1109/SANER50967.2021.00026 |
| P193 |
DiFuzzNMT: A Differential Fuzzing Framework for Neural Machine Translation Haibo Chen, Jinfu Chen, Saihua Cai, Shengran Wang, Jingyi Chen BibKey: chen_difuzznmt_2025
|
2025 | QRS International Conference on Software Quality, Reliability and Security |
DOI10.1109/QRS65678.2025.00064 |
| P197 |
Perception-Guided Fuzzing for Simulated Scenario-Based Testing of Autonomous Driving Systems Tri Minh Triet Pham, Bo Yang, Jinqiu Yang BibKey: pham_perception-guided_2024
|
2024 | arXiv arXiv.org |
DOI10.48550/arXiv.2408.13686 |
| P198 |
Semantic-Guided Fuzzing for Virtual Testing of Autonomous Driving Systems An Guo, Yang Feng, Yizhen Cheng, Zhenyu Chen BibKey: guo_semantic-guided_2024
|
2024 | JSS Journal of Systems and Software |
DOI10.1016/j.jss.2024.112017 |
| P200 |
TSDTest: A Efficient Coverage Guided Two-Stage Testing for Deep Learning Systems Hao Li, Shihai Wang, Tengfei Shi, Xinyue Fang, Jian Chen BibKey: li_tsdtest_2022
|
2022 | QRS Companion IEEE International Conference on Software Quality, Reliability and Security Companion |
DOI10.1109/QRS-C57518.2022.00033 |
| P201 |
DeepMC: DNN Test Sample Optimization Method Jointly Guided by Misclassification and Coverage Jiaze Sun, Juan Li, Sulei Wen BibKey: sun_deepmc_2023
|
2022 | Applied Intelligence Applied intelligence (Boston) |
DOI10.1007/s10489-022-04323-4 |
| P202 |
DANCe: Dynamic Adaptive Neuron Coverage for Fuzzing Deep Neural Networks Aoshuang Ye, Lina Wang, Lei Zhao, Jianpeng Ke BibKey: ye_dance_2022
|
2022 | IJCNN IEEE International Joint Conference on Neural Network |
DOI10.1109/IJCNN55064.2022.9892349 |
| P204 |
Coverage Guided Differential Adversarial Testing of Deep Learning Systems Jianmin Guo, H. Song, Yue Zhao, Yu Jiang BibKey: guo_coverage_2021
|
2021 | TNSE IEEE Transactions on Network Science and Engineering |
DOI10.1109/tnse.2020.2997359 |
| P208 |
Fuzzing-Based Hard-Label Black-Box Attacks against Machine Learning Models Yi Qin, Chuan Yue BibKey: qin_fuzzing-based_2022
|
2019 | Computers & Security | DOI10.1016/j.cose.2022.102694 |
The complete machine-readable study metadata, normalized taxonomy labels, screening records, and annotation materials are available in the replication package.