Fetching the paper…
Reading the bibliography…
Compiler correctness is crucial, as miscompilation can falsify program behaviors, leading to serious consequences.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901
Earlier work this paper cites.
On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
William R Thompson. 1933 · 1933
Earlier work this paper cites.
Symbolic execution and program testing
James C King. 1976 · 1976
Earlier work this paper cites.
A generalization of the beta distribution with applications
James B McDonald and Yexiao J Xu. 1995 · 1995
Earlier work this paper cites.
Differential testing for software
William M McKeeman. 1998 · 1998
Earlier work this paper cites.
LLVM: A compilation framework for lifelong program analysis & transformation. In
Chris Lattner and Vikram Adve. 2004 · 2004
Earlier work this paper cites.
DART: Directed Automated Random Testing. In
Patrice Godefroid, Nils Klarlund, and Koushik Sen. 2005 · 2005
Earlier work this paper cites.
CUTE: A Concolic Unit Testing Engine for C. In
Koushik Sen, Darko Marinov, and Gul Agha. 2005 · 2005
Earlier work this paper cites.
jsfunfuzz
Mozilla Security. 2007 · 2007
Earlier work this paper cites.
Concolic testing. In
Koushik Sen. 2007 · 2007
Earlier work this paper cites.
Fuzzing: brute force vulnerability discovery
Michael Sutton, Adam Greene, and Pedram Amini. 2007 · 2007
Earlier work this paper cites.
OpenGL programming guide: the official guide to learning OpenGL, versions 3.0 and 3.1
Dave Shreiner et al · 2009
Earlier work this paper cites.
Evosuite: automatic test suite generation for object-oriented software. In
Gordon Fraser and Andrea Arcuri. 2011 · 2011
Earlier work this paper cites.
Finding and understanding bugs in C compilers. In
Xuejun Yang, Yang Chen, Eric Eide, and John Regehr. 2011 · 2011
Earlier work this paper cites.
Fuzzing with code fragments. In
Christian Holler, Kim Herzig, and Andreas Zeller. 2012 · 2012
Earlier work this paper cites.
Coverage is not strongly correlated with test suite effectiveness. In
Laura Inozemtseva and Reid Holmes. 2014 · 2014
Earlier work this paper cites.
Compiler validation via equivalence modulo inputs
Vu Le, Mehrdad Afshari, and Zhendong Su. 2014 · 2014
Earlier work this paper cites.
Finding deep compiler bugs via guided stochastic program mutation
Vu Le, Chengnian Sun, and Zhendong Su. 2015 · 2015
Earlier work this paper cites.
Identity mappings in deep residual networks. In
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Earlier work this paper cites.
Toward understanding compiler bugs in GCC and LLVM. In
Chengnian Sun, Vu Le, Qirun Zhang, and Zhendong Su. 2016 · 2016
Earlier work this paper cites.
Automated testing of graphics shader compilers
Alastair F Donaldson, Hugues Evrard, Andrei Lascu, and Paul Thomson. 2017 · 2017
Earlier work this paper cites.
Deepxplore: Automated whitebox testing of deep learning systems. In
Kexin Pei, Yinzhi Cao, Junfeng Yang, and Suman Jana. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Dead store elimination (still) considered harmful. In
Zhaomo Yang, Brian Johannesmeyer, Anders Trier Olesen, Sorin Lerner, and Kirill Levchenko. 2017 · 2017
Earlier work this paper cites.
Skeletal program enumeration for rigorous compiler testing. In
Qirun Zhang, Chengnian Sun, and Zhendong Su. 2017 · 2017
Earlier work this paper cites.
Deep learning using rectified linear units (relu)
Abien Fred Agarap. 2018 · 2018
Earlier work this paper cites.
{ \{ TVM
Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, et al · 2018
Earlier work this paper cites.
Evaluating fuzz testing. In
George Klees, Andrew Ruef, Benji Cooper, Shiyi Wei, and Michael Hicks. 2018 · 2018
Earlier work this paper cites.
{ \{ QSYM
Insu Yun, Sangho Lee, Meng Xu, Yeongjin Jang, and Taesoo Kim. 2018 · 2018
Earlier work this paper cites.
Intriguer: Field-level constraint solving for hybrid fuzzing. In
Mingi Cho, Seoyoung Kim, and Taekyoung Kwon. 2019 · 2019
Cited alongside, same era.
Grey-box concolic testing on binary code. In
Jaeseung Choi, Joonun Jang, Choongwoo Han, and Sang Kil Cha. 2019 · 2019
Cited alongside, same era.
CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning Libraries. In
Hung Viet Pham, Thibaud Lutellier, Weizhen Qi, and Lin Tan. 2019 · 2019
Cited alongside, same era.
The fuzzing book
Andreas Zeller, Rahul Gopinath, Marcel Böhme, Gordon Fraser, and Christian Holler. 2019 · 2019
Cited alongside, same era.
A survey of compiler testing
Junjie Chen, Jibesh Patra, Michael Pradel, Yingfei Xiong, Hongyu Zhang, Dan Hao, and Lu Zhang. 2020 · 2020
Cited alongside, same era.
Codebert: A pre-trained model for programming and natural languages
GrayC: Greybox Fuzzing of Compilers and Analysers for C
Karine Even-Mendoza, Arindam Sharma, Alastair F Donaldson, and Cristian Cadar. 2023 · 2023
Closest in time.
Hugging Face
HuggingFace 2023 · 2023
Closest in time.
Evaluating and improving hybrid fuzzing. In
Ling Jiang, Hengchen Yuan, Mingyuan Wu, Lingming Zhang, and Yuqun Zhang. 2023 · 2023
Closest in time.
CODAMOSA: Escaping coverage plateaus in test generation with pre-trained large language models. In
Caroline Lemieux, Jeevana Priya Inala, Shuvendu K Lahiri, and Siddhartha Sen. 2023 · 2023
Closest in time.
StarCoder: may the source be with you!
Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al · 2023
Closest in time.
PyRTFuzz: Detecting Bugs in Python Runtimes via Two-Level Collaborative Fuzzing. In
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, et al · 2020
Cited alongside, same era.
Fuzzing with fast failure feedback
Rahul Gopinath, Bachir Bendrissou, Björn Mathis, and Andreas Zeller. 2020 · 2020
Cited alongside, same era.
Audee: Automated testing for deep learning frameworks. In
Qianyu Guo, Xiaofei Xie, Yi Li, Xiaoyu Zhang, Yang Liu, Xiaohong Li, and Chao Shen. 2020 · 2020
Cited alongside, same era.
Pangolin: Incremental hybrid fuzzing with polyhedral path abstraction. In
Heqing Huang, Peisen Yao, Rongxin Wu, Qingkai Shi, and Charles Zhang. 2020 · 2020
Cited alongside, same era.
HFL: Hybrid Fuzzing on the Linux Kernel.. In
Kyungtae Kim, Dae R Jeong, Chung Hwan Kim, Yeongjin Jang, Insik Shin, and Byoungyoung Lee. 2020 · 2020
Cited alongside, same era.
Random testing for C and C++ compilers with YARPGen
Vsevolod Livinskii, Dmitry Babokin, and John Regehr. 2020 · 2020
Cited alongside, same era.
Learning input tokens for effective fuzzing. In
Björn Mathis, Rahul Gopinath, and Andreas Zeller. 2020 · 2020
Cited alongside, same era.
Wen Li, Haoran Yang, Xiapu Luo, Long Cheng, and Haipeng Cai. 2023b · 2023
Closest in time.
libFuzzer – a library for coverage-guided fuzz testing
libFuzzer 2023 · 2023
Closest in time.
NeuRI: Diversifying DNN Generation via Inductive Rule Inference. In
Jiawei Liu, Jinjun Peng, Yuyao Wang, and Lingming Zhang. 2023c · 2023
Closest in time.
Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2023a · 2023
Closest in time.
DSFuzz: Detecting Deep State Bugs with Dependent State Exploration. In
Yinxi Liu and Wei Meng. 2023 · 2023
Closest in time.
LLVM’s Analysis and Transform Passes
LLVM 2023 · 2023
Closest in time.
Learning Deep Semantics for Test Completion
Pengyu Nie, Rahul Banerjee, Junyi Jessy Li, Raymond J Mooney, and Milos Gligoric. 2023 · 2023
Closest in time.
Adaptive test generation using a large language model
Max Schäfer, Sarah Nadi, Aryaz Eghbali, and Frank Tip. 2023 · 2023
Closest in time.
An Empirical Study of Bugs in Open-Source Federated Learning Framework
Weijie Shao, Yuyang Gao, Fu Song, Sen Chen, and Lingling Fan. 2023 · 2023
Closest in time.
SMT Solver Validation Empowered by Large Pre-trained Language Models. In
Maolin Sun, Yibiao Yang, Yang Wang, Ming Wen, Haoxiang Jia, and Yuming Zhou. 2023 · 2023
Closest in time.
TensorFlow
TensorFlow 2023 · 2023
Closest in time.
TensorFlow Lite
TensorFlowLite 2023 · 2023
Closest in time.
TensorFlow XLA
TensorFlowXLA 2023 · 2023
Closest in time.
Universal fuzzing via large language models
Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, and Lingming Zhang. 2023 · 2023
Closest in time.
Silent Bugs Matter: A Study of
Jianhao Xu, Kangjie Lu, Zhengjie Du, Zhu Ding, Linke Li, Qiushi Wu, Mathias Payer, and Bing Mao. 2023 · 2023
Closest in time.
Kernelgpt: Enhanced kernel fuzzing via large language models
Chenyuan Yang, Zijie Zhao, and Lingming Zhang. 2023b · 2023
Closest in time.
A survey on large language models for software engineering
Quanjun Zhang, Chunrong Fang, Yang Xie, Yaxin Zhang, Yun Yang, Weisong Sun, Shengcheng Yu, and Zhenyu Chen. 2023 · 2023
Closest in time.
ChatUniTest: A Framework for LLM-Based Test Generation. In
Yinghao Chen, Zehao Hu, Chen Zhi, Junxiao Han, Shuiguang Deng, and Jianwei Yin. 2024 · 2024
Closest in time.
Effective test generation using pre-trained large language models and mutation testing
Arghavan Moradi Dakhel, Amin Nikanjam, Vahid Majdinasab, Foutse Khomh, and Michel C Desmarais. 2024 · 2024
Closest in time.
Large language models based fuzzing techniques: A survey
Linghan Huang, Peizhou Zhao, Huaming Chen, and Lei Ma. 2024 · 2024
Closest in time.
Large language model guided protocol fuzzing. In
Ruijie Meng, Martin Mirchev, Marcel Böhme, and Abhik Roychoudhury. 2024 · 2024
Closest in time.
The Mutators Reloaded: Fuzzing Compilers with Large Language Model Generated Mutation Operators
Xianfei Ou, Cong Li, Yanyan Jiang, and Chang Xu. 2024 · 2024
Closest in time.
Chatgpt vs sbst: A comparative assessment of unit test suite generation
Yutian Tang, Zhijie Liu, Zhichao Zhou, and Xiapu Luo. 2024 · 2024
Closest in time.
Magicoder: Empowering code generation with oss-instruct. In
Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, and Lingming Zhang. 2024 · 2024
Closest in time.