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Deep learning (DL) models of code have recently reported great progress for vulnerability detection.
The distribution of the flora in the alpine zone.1
Paul Jaccard · 1912
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A complexity measure
T.J. McCabe · 1976
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Typestate: A programming language concept for enhancing software reliability
Robert E. Strom and Shaula Yemini · 1986
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TAJ: effective taint analysis of web applications
Omer Tripp, Marco Pistoia, Stephen J. Fink, Manu Sridharan, and Omri Weisman · 2009
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“Why Should I Trust You?”: Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan · 2017
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VulDeePecker: A deep learning-based system for vulnerability detection
Zhen Li, Deqing Zou, Shouhuai Xu, Xinyu Ou, Hai Jin, Sujuan Wang, Zhijun Deng, and Yuyi Zhong · 2018
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Code2vec: Learning distributed representations of code
Uri Alon, Meital Zilberstein, Omer Levy, and Eran Yahav · 2019
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A performance evaluation of deep‐learnt features for software vulnerability detection
Xinbo Ban, Shigang Liu, Chao Chen, and Caslon Chua · 2019
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Automated Vulnerability Detection in Source Code Using Deep Representation Learning
Rebecca Russell, Louis Kim, Lei Hamilton, Tomo Lazovich, Jacob Harer, Onur Ozdemir, Paul Ellingwood, and Marc McConley · 2019
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GNN explainer: A tool for post-hoc explanation of graph neural networks
Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, and Jure Leskovec · 2019
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A Novel Neural Source Code Representation Based on Abstract Syntax Tree
Jian Zhang, Xu Wang, Hongyu Zhang, Hailong Sun, Kaixuan Wang, and Xudong Liu · 2019
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Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks
Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu · 2019
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Hoppity: Learning graph transformations to detect and fix bugs in programs
Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, and Ke Wang · 2020
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A C/C++ code vulnerability dataset with code changes and cve summaries
Jiahao Fan, Yi Li, Shaohua Wang, and Tien N. Nguyen · 2020
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CodeBERT: A pre-trained model for programming and natural languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou · 2020
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Global relational models of source code
Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, and David Bieber · 2020
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Software Vulnerability Detection Using Deep Neural Networks: A Survey
Guanjun Lin, Sheng Wen, Qing-Long Han, Jun Zhang, and Yang Xiang · 2020
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A Comparative Study of Neural Network Techniques for Automatic Software Vulnerability Detection
Gaigai Tang, Lianxiao Meng, Huiqiang Wang, Shuangyin Ren, Qiang Wang, Lin Yang, and Weipeng Cao · 2020
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The language interpretability tool: Extensible, interactive visualizations and analysis for NLP models
Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, and Ann Yuan · 2020
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Unified pre-training for program understanding and generation, 2021
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang · 2021
Cited alongside, same era.
Xin Wang, Yasheng Wang, Fei Mi, Pingyi Zhou, Yao Wan, Xiao Liu, Li Li, Hao Wu, Jin Liu, and Xin Jiang · 2021
Later among the works it cites.
D2a: A dataset built for ai-based vulnerability detection methods using differential analysis
Yunhui Zheng, Saurabh Pujar, Burn Lewis, Luca Buratti, Edward Epstein, Bo Yang, Jim Laredo, Alessandro Morari, and Zhong Su · 2021
Later among the works it cites.
Mvd: Memory-related vulnerability detection based on flow-sensitive graph neural networks
Sicong Cao, Xiaobing Sun, Lili Bo, Rongxin Wu, Bin Li, and Chuanqi Tao · 2022
Closest in time.
Deep learning based vulnerability detection: Are we there yet?
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, and Baishakhi Ray · 2022
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Velvet: a novel ensemble learning approach to automatically locate vulnerable statements, 2022
Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail Kaiser, and Baishakhi Ray · 2022
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BGNN4VD: Constructing Bidirectional Graph Neural-Network for Vulnerability Detection
Sicong Cao, Xiaobing Sun, Lili Bo, Ying Wei, and Bin Li · 2021
Cited alongside, same era.
DeepWukong: Statically Detecting Software Vulnerabilities Using Deep Graph Neural Network
Xiao Cheng, Haoyu Wang, Jiayi Hua, Guoai Xu, and Yulei Sui · 2021
Cited alongside, same era.
On using distributed representations of source code for the detection of C security vulnerabilities, 2021
David Coimbra, Sofia Reis, Rui Abreu, Corina Păsăreanu, and Hakan Erdogmus · 2021
Cited alongside, same era.
Towards learning (dis)-similarity of source code from program contrasts, 2021
Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, and Saikat Chakraborty · 2021
Cited alongside, same era.
Project codenet, 2021
IBM · 2021
Cited alongside, same era.
Vulnerability detection with fine-grained interpretations
Yi Li, Shaohua Wang, and Tien N. Nguyen · 2021
Cited alongside, same era.
Deep neural-based vulnerability discovery demystified: data, model and performance
Guanjun Lin, Wei Xiao, Leo Yu Zhang, Shang Gao, Yonghang Tai, and Jun Zhang · 2021
Cited alongside, same era.
Closest in time.
LineVul: A transformer-based line-level vulnerability prediction
Michael Fu and Chakkrit Tantithamthavorn · 2022
Closest in time.
VulBERTa: Simplified source code pre-training for vulnerability detection
Hazim Hanif and Sergio Maffeis · 2022
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LineVD: Statement-level vulnerability detection using graph neural networks, 2022
David Hin, Andrey Kan, Huaming Chen, and M. Ali Babar · 2022
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VulDeeLocator: A deep learning-based fine-grained vulnerability detector
Zhen Li, Deqing Zou, Shouhuai Xu, Zhaoxuan Chen, Yawei Zhu, and Hai Jin · 2022
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SySeVR: A framework for using deep learning to detect software vulnerabilities
Zhen Li, Deqing Zou, Shouhuai Xu, Hai Jin, Yawei Zhu, and Zhaoxuan Chen · 2022
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Competitive programming with alphacode, 2022
Deep Mind · 2022
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ReGVD: Revisiting graph neural networks for vulnerability detection
Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, and Dinh Phung · 2022
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HGVul: A code vulnerability detection method based on heterogeneous source-level intermediate representation
Zihua Song, Junfeng Wang, Shengli Liu, Zhiyang Fang, Kaiyuan Yang, and Gu Zhaoquan · 2022
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VulCNN: an image-inspired scalable vulnerability detection system
Yueming Wu, Deqing Zou, Shihan Dou, Wei Yang, Duo Xu, and Hai Jin · 2022
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ACGDP: An Augmented Code Graph-Based System for Software Defect Prediction
Jiaxi Xu, Jun Ai, Jingyu Liu, and Tao Shi · 2022
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