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In recent years, artificial intelligence has had a conspicuous growth in almost every aspect of life.
Llmseceval: A dataset of natural language prompts for security evaluations
Catherine Tony, Markus Mutas, Nicolás E Díaz Ferreyra, and Riccardo Scandariato · 2014
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https://www.cvedetails.com/browse-by-date.php , 2023
cvedetails · 2015
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Vccfinder: Finding potential vulnerabilities in open-source projects to assist code audits
Perl H, Dechand S, Smith M, Arp D, Yamaguchi, Rieck K, and et al · 2015
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Pyt: A static analysis tool for detecting security vulnerabilities in python web applications, 2016
Bruno Thalmann Stefan Micheelsen · 2016
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Automated identification of security issues from commit messages and bug reports
Sharma A. Zhou Y · 2017
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Automated vulnerability detection in source code using deep representation learning
Rebecca Russell and et al. Kim · 2018
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Vuldeepecker: A deep learning-based system for vulnerability detection
Zhen Li and et al. Zou · 2018
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An efficient user identification approach based on netflow analysis
Atieh Bakhshandeh and Zahra Eskandari · 2018
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Effective vulnerability identification by learning comprehensive program semantics via graph neural networks
Zhou Y., Liu S., Siow J, Du X, and Liu Y. Devign · 2019
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Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks
et al. Zhou, Yaqin · 2019
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Tfix: Learning to fix coding errors with a text-to-text transformer
Berabi B, He J, Raychev V, and Vechev M · 2021
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Machine learning in the context of static application security testing - ml-sast
Lorenz Hüther, Bernhard J. Berger, Stefan Edelkamp, Sebastian Eken, Lara Luhrmann, and et al Hendrik Rothe · 2021
Cited alongside, same era.
Machine learning techniques for software vulnerability prediction: a comparative study
Jabeen G, Rahim S, Afzal W, Khan D, Khan A, Hussain Z, and et al · 2022
Cited alongside, same era.
Vulberta: Simplified source code pre-training for vulnerability detection
Maffeis S. Hanif H · 2022
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Graph neural networks: a bibliometrics overview
Abdalsamad Keramatfar, Mohadeseh Rafiee, and Hossein Amirkhani · 2022
Cited alongside, same era.
Deep learning based vulnerability detection: Are we there yet?
Chakraborty S, Krishna R, and Ding Yand Ray B · 2022
Cited alongside, same era.
Vulrepair: A t5-based automated software vulnerability repair
Vulberta: Simplified source code pre-training for vulnerability detection
Hazim Hanif and Sergio Maffeis · 2022
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Linevul: a transformer-based line-level vulnerability prediction
Michael Fu and Chakkrit Tantithamthavorn · 2022
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Securityeval dataset: mining vulnerability examples to evaluate machine learning-based code generation techniques
Mohammed Latif Siddiq and Joanna CS Santos · 2022
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https://en.wikipedia.org/wiki/GitHub , 2023
Wikipedia · 2023
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A hybrid approach for evaluation and prioritization of software vulnerabilities
Kumar V, Anjum M, Agarwal V, and Kapur PK · 2023
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https://spectrum.ieee.org/top-programming-languages-2022 , 2022
spectrum · 2023
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Fu Michael and et al · 2022
Cited alongside, same era.
Velvet: a novel ensemble learning approach to automatically locate vulnerable statements
et al. Ding, Yangruibo · 2022
Cited alongside, same era.
Just-in-time software vulnerability detection: Are we there yet?
et al. Lomio, Francesco · 2022
Cited alongside, same era.
Vudenc: Vulnerability detection with deep learning on a natural codebase for python
Laura Wartschinski and et al. Nollers · 2022
Cited alongside, same era.
An empirical study of deep learning models for vulnerability detection
et al. Steenhoek, Benjamin · 2022
Cited alongside, same era.
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Diversevul: A new vulnerable source code dataset for deep learning based vulnerability detection
et al. Chen, Yizheng · 2023
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Evaluation of chatgpt model for vulnerability detection
Pavel Zadorozhny Cheshkov, Anton and Rodion Levichev · 2023
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https://github.com/python-security/pyt/tree/master/examples , 2018
python-security · 2023
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Chatgpt prompt engineering for developers
Isa Fulford Andrew Ng · 2023
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