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Vulnerability analysis is crucial for software security.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
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Modeling and Discovering Vulnerabilities with Code Property Graphs. In Proceedings of the 2014 IEEE Symposium on Security and Privacy . 590–604
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You Get Where You’re Looking for: The Impact of Information Sources on Code Security. In Proceedings of the 2016 IEEE Symposium on Security and Privacy . 289–305
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Neural Machine Translation of Rare Words with Subword Units. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics Volume 1: Long Papers
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Rabe Abdalkareem, Emad Shihab, and Juergen Rilling. 2017 · 2017
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Stack overflow considered harmful? the impact of copy&paste on android application security. In Proceedings of the 2017 IEEE Symposium on Security and Privacy (SP) . 121–136
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Learning to Predict Severity of Software Vulnerability Using Only Vulnerability Description. In Proceedings of the 2017 IEEE International Conference on Software Maintenance and Evolution . 125–136
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Attention is All you Need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017 . 5998–6008
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VulDeePecker: A Deep Learning-Based System for Vulnerability Detection. In Proceedings of the 25th Annual Network and Distributed System Security Symposium
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Toward Validation of Textual Information Retrieval Techniques for Software Weaknesses. In Database and Expert Systems Applications - DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR (Communications in Computer and Information Science, Vol. 903) . 265–277
Jukka Ruohonen and Ville Leppänen. 2018 · 2018
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Automated Vulnerability Detection in Source Code Using Deep Representation Learning. In Proceedings of the 17th IEEE International Conference on Machine Learning and Applications . 757–762
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A Multi-Target Approach to Estimate Software Vulnerability Characteristics and Severity Scores
Georgios Spanos and Lefteris Angelis. 2018 · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 4171–4186
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Automated Software Vulnerability Assessment with Concept Drift. In Proceedings of the 2019 IEEE/ACM 16th International Conference on Mining Software Repositories . 371–382
Triet Huynh Minh Le, Bushra Sabir, and Muhammad Ali Babar. 2019 · 2019
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Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019 . 10197–10207
Yaqin Zhou, Shangqing Liu, Jing Kai Siow, Xiaoning Du, and Yang Liu. 2019 · 2019
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μ \mu VulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection
Deqing Zou, Sujuan Wang, Shouhuai Xu, Zhen Li, and Hai Jin. 2019 · 2019
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Automation of Vulnerability Classification from Its Description Using Machine Learning. In Proceedings of the 2020 IEEE Symposium on Computers and Communications . 1–7
Masaki Aota, Hideaki Kanehara, Masaki Kubo, Noboru Murata, Bo Sun, and Takeshi Takahashi. 2020 · 2020
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Language Models Are Few-Shot Learners. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020
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CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation. In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021
Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin B. Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, and Shujie Liu. 2021 · 2021
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Studying the Usage of Text-to-Text Transfer Transformer to Support Code-Related Tasks. In Proceedings of the 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) . 336–347
Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader Palacio, Denys Poshyvanyk, Rocco Oliveto, and Gabriele Bavota. 2021 · 2021
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CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing . 8696–8708
Yue Wang, Weishi Wang, Shafiq R. Joty, and Steven C. H. Hoi. 2021 · 2021
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A simple framework for contrastive learning of visual representations. In Proceedings of the 37th International Conference on Machine Learning . PMLR, 1597–1607
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020 · 2020
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ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. In Proceedings of the 8th International Conference on Learning Representations
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
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A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries. In Proceedings of the 17th International Conference on Mining Software Repositories . 508–512
Jiahao Fan, Yi Li, Shaohua Wang, and Tien N. Nguyen. 2020 · 2020
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CodeBERT: A Pre-Trained Model for Programming and Natural Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020 (Findings of ACL, Vol. EMNLP 2020) . 1536–1547
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou. 2020 · 2020
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Learning and Evaluating Contextual Embedding of Source Code. In International Conference on Machine Learning . 5110–5121
Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, and Kensen Shi. 2020 · 2020
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Big code != big vocabulary: open-vocabulary models for source code. In Proceedings of the 42nd International Conference on Software Engineering . 1073–1085
Rafael-Michael Karampatsis, Hlib Babii, Romain Robbes, Charles Sutton, and Andrea Janes. 2020 · 2020
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Multi-Task Learning Based Pre-Trained Language Model for Code Completion. In Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering . 473–485
Fang Liu, Ge Li, Yunfei Zhao, and Zhi Jin. 2020 · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Xin Zhou, DongGyun Han, and David Lo. 2021a · 2021
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Spi: Automated Identification of Security Patches via Commits
Yaqin Zhou, Jing Kai Siow, Chenyu Wang, Shangqing Liu, and Yang Liu. 2021c · 2021
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MVD: Memory-Related Vulnerability Detection Based on Flow-Sensitive Graph Neural Networks. In Proceedings of the 44th IEEE/ACM International Conference on Software Engineering . 1456–1468
Sicong Cao, Xiaobing Sun, Lili Bo, Rongxin Wu, Bin Li, and Chuanqi Tao. 2022 · 2022
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Deep Learning Based Vulnerability Detection: Are We There Yet?
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, and Baishakhi Ray. 2022b · 2022
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Towds Learning (Dis)-Similarity of Source Code from Program Contrasts. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 6300–6312
Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, and Saikat Chakraborty. 2022 · 2022
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UniXcoder: Unified Cross-Modal Pre-training for Code Representation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 7212–7225
Daya Guo, Shuai Lu, Nan Duan, Yanlin Wang, Ming Zhou, and Jian Yin. 2022 · 2022
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VulBERTa: Simplified Source Code Pre-Training for Vulnerability Detection. In Proceedings of the 2022 International Joint Conference on Neural Networks . 1–8
Hazim Hanif and Sergio Maffeis. 2022 · 2022
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Prompt-tuned code language model as a neural knowledge base for type inference in statically-typed partial code. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering . 1–13
Qing Huang, Zhiqiang Yuan, Zhenchang Xing, Xiwei Xu, Liming Zhu, and Qinghua Lu. 2022 · 2022
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On the Use of Fine-Grained Vulnerable Code Statements for Software Vulnerability Assessment Models. In Proceedings of the 19th International Conference on Mining Software Repositories . 621–633
Triet Huynh Minh Le and M. Ali Babar. 2022 · 2022
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Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
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SPT-Code: Sequence-to-Sequence Pre-Training for Learning Source Code Representations. In Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering . 1–13
Changan Niu, Chuanyi Li, Vincent Ng, Jidong Ge, Liguo Huang, and Bin Luo. 2022 · 2022
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AutoTransform: automated code transformation to support modern code review process. In Proceedings of the 44th International Conference on Software Engineering . 237–248
Patanamon Thongtanunam, Chanathip Pornprasit, and Chakkrit Tantithamthavorn. 2022 · 2022
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What do they capture? a structural analysis of pre-trained language models for source code. In Proceedings of the 44th International Conference on Software Engineering . 2377–2388
Yao Wan, Wei Zhao, Hongyu Zhang, Yulei Sui, Guandong Xu, and Hai Jin. 2022 · 2022
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CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training. In Findings of the Association for Computational Linguistics: NAACL 2022 . 1066–1077
Xin Wang, Yasheng Wang, Yao Wan, Jiawei Wang, Pingyi Zhou, Li Li, Hao Wu, and Jin Liu. 2022 · 2022
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CoditT5: Pretraining for Source Code and Natural Language Editing. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering . 1–12
Jiyang Zhang, Sheena Panthaplackel, Pengyu Nie, Junyi Jessy Li, and Milos Gligoric. 2022 · 2022
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National vulnerability database
2023 · 2023
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LongCoder: A Long-Range Pre-trained Language Model for Code Completion. In International Conference on Machine Learning, ICML 2023 (Proceedings of Machine Learning Research, Vol. 202) . PMLR, 12098–12107
Daya Guo, Canwen Xu, Nan Duan, Jian Yin, and Julian J. McAuley. 2023 · 2023
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A Survey on Data-driven Software Vulnerability Assessment and Prioritization
Triet Huynh Minh Le, Huaming Chen, and Muhammad Ali Babar. 2023 · 2023
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