Fetching the paper…
Reading the bibliography…
Software vulnerabilities bear enterprises significant costs.
Software engineering economics
Boehm Barry et al · 1981
Earlier work this paper cites.
BNR/NORTEL: path to improve product quality, reliability and customer satisfaction. In Proceedings of Sixth International Symposium on Software Reliability Engineering. ISSRE’95 . IEEE, 256–262
Walter Baziuk. 1995 · 1995
Earlier work this paper cites.
A Discipline of Software Engineering Addison-Wesley
W Humphrey. 1995 · 1995
Earlier work this paper cites.
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 · 2002
Earlier work this paper cites.
How can the developer benefit from security modeling?. In The Second International Conference on Availability, Reliability and Security (ARES’07) . IEEE, 1017–1025
Shanai Ardi, David Byers, Per Hakon Meland, Inger Anne Tondel, and Nahid Shahmehri. 2007 · 2007
Earlier work this paper cites.
Toward reducing fault fix time: Understanding developer behavior for the design of automated fault detection tools. In First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007) . IEEE, 176–185
Lucas Layman, Laurie Williams, and Robert St Amant. 2007 · 2007
Earlier work this paper cites.
Predicting vulnerable software components. In Proceedings of the 14th ACM conference on Computer and communications security . 529–540
Stephan Neuhaus, Thomas Zimmermann, Christian Holler, and Andreas Zeller. 2007 · 2007
Earlier work this paper cites.
Moving beyond security tracks: integrating security in cs0 and cs1. In Proceedings of the 39th SIGCSE technical symposium on Computer science education . 320–324
Blair Taylor and Shiva Azadegan. 2008 · 2008
Earlier work this paper cites.
A few billion lines of code later: using static analysis to find bugs in the real world
Al Bessey, Ken Block, Ben Chelf, Andy Chou, Bryan Fulton, Seth Hallem, Charles Henri-Gros, Asya Kamsky, Scott McPeak, and Dawson Engler. 2010 · 2010
Earlier work this paper cites.
ASIDE: IDE Support for Web Application Security. In Proceedings of the 27th Annual Computer Security Applications Conference (Orlando, Florida, USA) (ACSAC ’11) . Association for Computing Machinery, New York, NY, USA, 267–276
Jing Xie, Bill Chu, Heather Richter Lipford, and John T. Melton. 2011 · 2011
Earlier work this paper cites.
Building program vector representations for deep learning. In Knowledge Science, Engineering and Management: 8th International Conference, KSEM 2015, Chongqing, China, October 28-30, 2015, Proceedings 8 . Springer, 547–553
Hao Peng, Lili Mou, Ge Li, Yuxuan Liu, Lu Zhang, and Zhi Jin. 2015 · 2015
Earlier work this paper cites.
Bingo: Cross-architecture cross-os binary search. In Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering . 678–689
Mahinthan Chandramohan, Yinxing Xue, Zhengzi Xu, Yang Liu, Chia Yuan Cho, and Hee Beng Kuan Tan. 2016 · 2016
Earlier work this paper cites.
End-to-end prediction of buffer overruns from raw source code via neural memory networks
Min-je Choi, Sehun Jeong, Hakjoo Oh, and Jaegul Choo. 2017 · 2017
Earlier work this paper cites.
An NSA-derived ransomware worm is shutting down computers worldwide
Dan Goodin. 2017 · 2017
Earlier work this paper cites.
Learning binary code with deep learning to detect software weakness. In KSII the 9th international conference on internet (ICONI) 2017 symposium
Young Jun Lee, Sang-Hoon Choi, Chulwoo Kim, Seung-Ho Lim, and Ki-Woong Park. 2017 · 2017
Earlier work this paper cites.
Steelix: program-state based binary fuzzing. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering . 627–637
Yuekang Li, Bihuan Chen, Mahinthan Chandramohan, Shang-Wei Lin, Yang Liu, and Alwen Tiu. 2017 · 2017
Earlier work this paper cites.
Spain: security patch analysis for binaries towards understanding the pain and pills. In 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) . IEEE, 462–472
Zhengzi Xu, Bihuan Chen, Mahinthan Chandramohan, Yang Liu, and Fu Song. 2017 · 2017
Earlier work this paper cites.
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 · 2018
Earlier work this paper cites.
Automated vulnerability detection in source code using deep representation learning. In 2018 17th IEEE international conference on machine learning and applications (ICMLA) . IEEE, 757–762
Rebecca Russell, Louis Kim, Lei Hamilton, Tomo Lazovich, Jacob Harer, Onur Ozdemir, Paul Ellingwood, and Marc McConley. 2018 · 2018
Cited alongside, same era.
Towards security defect prediction with AI
Carson D Sestili, William S Snavely, and Nathan M VanHoudnos. 2018 · 2018
Cited alongside, same era.
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, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers) , Jill Burstein, Christy Doran, and Thamar Solorio (Eds.). Association for Computational Linguistics, 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Self-Attention based Automated Vulnerability Detection with Effective Data Representation. In 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) . 892–899
Tongshuai Wu, Liwei Chen, Gewangzi Du, Chenguang Zhu, and Gang Shi. 2021 · 2021
Later among the works it cites.
CWE List Version 4.9
2022 · 2022
Later among the works it cites.
Improving automatically generated code from Codex via Automated Program Repair
Zhiyu Fan, Xiang Gao, Abhik Roychoudhury, and Shin Hwei Tan. 2022 · 2022
Later among the works it cites.
LineVul: A Transformer-based Line-Level Vulnerability Prediction
Michael Fu and Chakkrit Tantithamthavorn. 2022 · 2022
Later among the works it cites.
GitHub Copilot· Your AI pair programmer
GitHub. 2022 · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tue Le, Tuan Nguyen, Trung Le, Dinh Phung, Paul Montague, Olivier De Vel, and Lizhen Qu. 2019 · 2019
Cited alongside, same era.
Cerebro: context-aware adaptive fuzzing for effective vulnerability detection. In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 533–544
Yuekang Li, Yinxing Xue, Hongxu Chen, Xiuheng Wu, Cen Zhang, Xiaofei Xie, Haijun Wang, and Yang Liu. 2019 · 2019
Cited alongside, same era.
Superion: Grammar-aware greybox fuzzing. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) . IEEE, 724–735
Junjie Wang, Bihuan Chen, Lei Wei, and Yang Liu. 2019 · 2019
Cited alongside, same era.
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 · 2019
Cited alongside, same era.
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation
David MW Powers. 2020 · 2020
Cited alongside, same era.
Intellicode compose: Code generation using transformer. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 1433–1443
Alexey Svyatkovskiy, Shao Kun Deng, Shengyu Fu, and Neel Sundaresan. 2020 · 2020
Cited alongside, same era.
Deep learning based vulnerability detection: Are we there yet
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, and Baishakhi Ray. 2021 · 2021
Cited alongside, same era.
Evaluating Large Language Models Trained on Code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021 · 2021
Cited alongside, same era.
CodeQL for research
Github Inc. 2021 · 2021
Cited alongside, same era.
CONFETTI: Amplifying Concolic Guidance for Fuzzers. In 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) . 438–450
James Kukucka, Luís Pina, Paul Ammann, and Jonathan Bell. 2022 · 2022
Later among the works it cites.
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
Later among the works it cites.
CWE - Common Weakness Enumeration
T. M. C. (MITRE). 2022 · 2022
Later among the works it cites.
A conversational paradigm for program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. 2022 · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Later among the works it cites.
Security Implications of Large Language Model Code Assistants: A User Study
Gustavo Sandoval, Hammond Pearce, Teo Nys, Ramesh Karri, Brendan Dolan-Gavitt, and Siddharth Garg. 2022 · 2022
Later among the works it cites.
An Empirical Study of Code Smells in Transformer-based Code Generation Techniques
Mohammed Latif Siddiq, Shafayat H Majumder, Maisha R Mim, Sourov Jajodia, and Joanna CS Santos. 2022 · 2022
Later among the works it cites.
Path Transitions Tell More:Optimizing Fuzzing Schedules via Runtime Program States
Kunpeng Zhang, Xi Xiao, Xiaogang Zhu, Ruoxi Sun, Minhui Xue, and Sheng Wen. 2022 · 2022
Later among the works it cites.
NATIONAL VULNERABILITY DATABASE
2023 · 2023
Closest in time.
Secure Development
2023 · 2023
Closest in time.
Microsoft Security Development Lifecycle
Microsoft Corp. 2023 · 2023
Closest in time.
"AI assistant for software developers"
TabNine. 2023 · 2023
Closest in time.