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Real-world programs expecting structured inputs often has a format-parsing stage gating the deeper program space.
Jcrasher: an automatic robustness tester for java
Christoph Csallner and Yannis Smaragdakis · 2004
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Feedback-directed random test generation
C. Pacheco, S. K. Lahiri, M. D. Ernst, and T. Ball · 2007
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Introducing jsfunfuzz
J. Ruderman · 2007
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Grammar-based whitebox fuzzing
Patrice Godefroid, Adam Kiezun, and Michael Y Levin · 2008
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Evosuite: Automatic test suite generation for object-oriented software
Gordon Fraser and Andrea Arcuri · 2011
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Finding and understanding bugs in c compilers
Xuejun Yang, Yang Chen, Eric Eide, and John Regehr · 2011
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Sage: whitebox fuzzing for security testing
Patrice Godefroid, Michael Y Levin, and David Molnar · 2012
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Software testing: A research travelogue (2000–2014)
Alessandro Orso and Gregg Rothermel · 2014
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Program-adaptive mutational fuzzing
Sang Kil Cha, Maverick Woo, and David Brumley · 2015
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Coverage-based greybox fuzzing as markov chain
Marcel Böhme, Van-Thuan Pham, and Abhik Roychoudhury · 2016
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Lava: Large-scale automated vulnerability addition
Brendan Dolan-Gavitt, Patrick Hulin, Engin Kirda, Tim Leek, Andrea Mambretti, Wil Robertson, Frederick Ulrich, and Ryan Whelan · 2016
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Learning to fuzz: Application-independent fuzz testing with probabilistic, generative models of input data
Jibesh Patra and Michael Pradel · 2016
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Driller: Augmenting fuzzing through selective symbolic execution
Nick Stephens, John Grosen, Christopher Salls, Andrew Dutcher, Ruoyu Wang, Jacopo Corbetta, Yan Shoshitaishvili, Christopher Kruegel, and Giovanni Vigna · 2016
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Directed greybox fuzzing
Marcel Böhme, Van-Thuan Pham, Manh-Dung Nguyen, and Abhik Roychoudhury · 2017
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Oss-fuzz: Five months later, and rewarding projects
Oliver Chang, Abhishek Arya, Kostya Serebryany, and Josh Armour · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Fairfuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage
Caroline Lemieux and Koushik Sen · 2018
Cited alongside, same era.
Inferring input grammars from dynamic control flow, 2019
Rahul Gopinath, Björn Mathis, and Andreas Zeller · 2019
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Building fast fuzzers, 2019
Rahul Gopinath and Andreas Zeller · 2019
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Codealchemist: Semantics-aware code generation to find vulnerabilities in javascript engines
HyungSeok Han, DongHyeon Oh, and Sang Kil Cha · 2019
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Afl++ combining incremental steps of fuzzing research
Andrea Fioraldi, Dominik Maier, Heiko Eißfeldt, and Marc Heuse · 2020
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Mtfuzz: Fuzzing with a multi-task neural network
Dongdong She, Rahul Krishna, Lu Yan, Suman Jana, and Baishakhi Ray · 2020
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Unifuzz: A holistic and pragmatic metrics-driven platform for evaluating fuzzers
Yuwei Li, Shouling Ji, Yuan Chen, Sizhuang Liang, Wei-Han Lee, Yueyao Chen, Chenyang Lyu, Chunming Wu, Raheem Beyah, Peng Cheng, et al · 2021
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Token-Level Fuzzing
Christopher Salls, Chani Jindal, Jake Corina, Christopher Kruegel, and Giovanni Vigna · 2021
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Unit test case generation with transformers and focal context, 2021
Michele Tufano, Dawn Drain, Alexey Svyatkovskiy, Shao Kun Deng, and Neel Sundaresan · 2021
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https://google.github.io/fuzzbench , 2022
Fuzzbench: Fuzzer benchmarking as a service · 2022
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Saffron: Adaptive grammar-based fuzzing for worst-case analysis
Xuan-Bach D. Le, Corina S. Pasareanu, Rohan Padhye, David Lo, Willem Visser, and Koushik Sen · 2019
Cited alongside, same era.
Mopt: Optimized mutation scheduling for fuzzers
Chenyang Lyu, Shouling Ji, Chao Zhang, Yuwei Li, Wei-Han Lee, Yu Song, and Raheem Beyah · 2019
Cited alongside, same era.
Semantic fuzzing with zest
Rohan Padhye, Caroline Lemieux, Koushik Sen, Mike Papadakis, and Yves Le Traon · 2019
Cited alongside, same era.
Neuzz: Efficient fuzzing with neural program smoothing
Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, and Suman Jana · 2019
Cited alongside, same era.
Superion: Grammar-aware greybox fuzzing
Junjie Wang, Bihuan Chen, Lei Wei, and Yang Liu · 2019
Cited alongside, same era.
https://github.com/mozillasecurity/dharma , 2020
Mozilla security - dharma · 2020
Cited alongside, same era.
Later among the works it cites.
Code generation tools (almost) for free? a study of few-shot, pre-trained language models on code, 2022
Patrick Bareiß, Beatriz Souza, Marcelo d’Amorim, and Michael Pradel · 2022
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{ \{ SYMSAN } \} : Time and space efficient concolic execution via dynamic data-flow analysis
Ju Chen, Wookhyun Han, Mingjun Yin, Haochen Zeng, Chengyu Song, Byoungyoung Lee, Heng Yin, and Insik Shin · 2022
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Jigsaw: Large language models meet program synthesis
Naman Jain, Skanda Vaidyanath, Arun Iyer, Nagarajan Natarajan, Suresh Parthasarathy, Sriram Rajamani, and Rahul Sharma · 2022
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Evaluating and improving neural program-smoothing-based fuzzing
Mingyuan Wu, Ling Jiang, Jiahong Xiang, Yuqun Zhang, Guowei Yang, Huixin Ma, Sen Nie, Shi Wu, Heming Cui, and Lingming Zhang · 2022
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Large language models are edge-case fuzzers: Testing deep learning libraries via fuzzgpt
Yinlin Deng, Chunqiu Steven Xia, Chenyuan Yang, Shizhuo Dylan Zhang, Shujing Yang, and Lingming Zhang · 2023
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Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models
Caroline Lemieux, Jeevana Priya Inala, Shuvendu K Lahiri, and Siddhartha Sen · 2023
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Chatunitest: a chatgpt-based automated unit test generation tool
Zhuokui Xie, Yinghao Chen, Chen Zhi, Shuiguang Deng, and Jianwei Yin · 2023
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