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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automated Vulnerability Detection in Source Code Using Minimum Intermediate Representation Learning
Xin Li, Lu Wang, Yang Xin, et al.
Applied Sciences (2020) Vol. 10, Iss. 5, pp. 1692-1692
Open Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

A Holistic Review of Cybersecurity and Reliability Perspectives in Smart Airports
Nickolaos Koroniotis, Nour Moustafa, Francesco Schiliro, et al.
IEEE Access (2020) Vol. 8, pp. 209802-209834
Open Access | Times Cited: 118
The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches
Hazim Hanif, Mohd Hairul Nizam Md Nasir, Mohd Faizal Ab Razak, et al.
Journal of Network and Computer Applications (2021) Vol. 179, pp. 103009-103009
Closed Access | Times Cited: 98
CVEfixes: automated collection of vulnerabilities and their fixes from open-source software
Guru Prasad Bhandari, Amara Naseer, Leon Moonen
(2021), pp. 30-39
Open Access | Times Cited: 92
Transformer-Based Language Models for Software Vulnerability Detection
Chandra Thapa, Seung Ick Jang, Muhammad Ejaz Ahmed, et al.
(2022)
Closed Access | Times Cited: 56
Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology
Allison Chae, Michael S. Yao, Hersh Sagreiya, et al.
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 10
Codeguard: Utilizing Advanced Pattern Recognition in Language Models for Software Vulnerability Analysis
Rebet Jones, Marwan Omar
Revista Academiei Forţelor Terestre (2024) Vol. 29, Iss. 1, pp. 108-118
Open Access | Times Cited: 8
Software Vulnerability Analysis and Discovery Using Deep Learning Techniques: A Survey
Peng Zeng, Guanjun Lin, Lei Pan, et al.
IEEE Access (2020) Vol. 8, pp. 197158-197172
Open Access | Times Cited: 60
AutoVAS: An automated vulnerability analysis system with a deep learning approach
Sanghoon Jeon, Huy Kang Kim
Computers & Security (2021) Vol. 106, pp. 102308-102308
Closed Access | Times Cited: 41
SedSVD: Statement-level software vulnerability detection based on Relational Graph Convolutional Network with subgraph embedding
Yukun Dong, Yeer Tang, Xiaotong Cheng, et al.
Information and Software Technology (2023) Vol. 158, pp. 107168-107168
Closed Access | Times Cited: 20
VulDetect: A novel technique for detecting software vulnerabilities using Language Models
Marwan Omar, Stavros Shiaeles
(2023), pp. 105-110
Closed Access | Times Cited: 20
Software Vulnerability Detection using Large Language Models
Moumita Das Purba, Arpita Ghosh, Benjamin J. Radford, et al.
(2023), pp. 112-119
Closed Access | Times Cited: 20
CrossVul: a cross-language vulnerability dataset with commit data
Georgios Nikitopoulos, Konstantina Dritsa, Πάνος Λουρίδας, et al.
(2021)
Closed Access | Times Cited: 37
A novel approach for software vulnerability detection based on intelligent cognitive computing
Cho Do Xuan, Dao Hoang, Ma Cong Thanh, et al.
The Journal of Supercomputing (2023) Vol. 79, Iss. 15, pp. 17042-17078
Closed Access | Times Cited: 13
SIFT: enhance the performance of vulnerability detection by incorporating structural knowledge and multi-task learning
Liping Wang, Guilong Lu, Xiang Chen, et al.
Automated Software Engineering (2025) Vol. 32, Iss. 2
Closed Access
Automated Software Vulnerability Detection Based on Hybrid Neural Network
Xin Li, Lu Wang, Yang Xin, et al.
Applied Sciences (2021) Vol. 11, Iss. 7, pp. 3201-3201
Open Access | Times Cited: 27
Vulnerability detection in Java source code using a quantum convolutional neural network with self-attentive pooling, deep sequence, and graph-based hybrid feature extraction
Shumaila Hussain, Muhammad Nadeem, Junaid Baber, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
A New Framework for Software Vulnerability Detection Based on an Advanced Computing
Bùi Văn Cong, Cho Do Xuan
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 3, pp. 3699-3723
Open Access | Times Cited: 4
DMVL4AVD: a deep multi-view learning model for automated vulnerability detection
Xiaozhi Du, Yanrong Zhou, Hongyuan Du
Neural Computing and Applications (2025)
Closed Access
A Survey of Source Code Representations for Machine Learning-Based Cybersecurity Tasks
Beatrice Casey, Joanna C. S. Santos, George Perry
ACM Computing Surveys (2025)
Open Access
Review of NLP-based Systems in Digital Forensics and Cybersecurity
David Okore Ukwen, Murat Karabatak
(2021) Vol. 7, pp. 1-9
Closed Access | Times Cited: 25
Detecting vulnerabilities in IoT software: New hybrid model and comprehensive data analysis
Huan Mei, Guanjun Lin, Fang Da, et al.
Journal of Information Security and Applications (2023) Vol. 74, pp. 103467-103467
Closed Access | Times Cited: 10
Machine Learning for Source Code Vulnerability Detection: What Works and What Isn’t There Yet
Tina Marjanov, Ivan Pashchenko, Fabio Massacci
IEEE Security & Privacy (2022) Vol. 20, Iss. 5, pp. 60-76
Open Access | Times Cited: 15
Open Science in Software Engineering: A Study on Deep Learning-Based Vulnerability Detection
Yu Nong, Rainy Sharma, Abdelwahab Hamou‐Lhadj, et al.
IEEE Transactions on Software Engineering (2022) Vol. 49, Iss. 4, pp. 1983-2005
Closed Access | Times Cited: 15
Machine learning techniques for software vulnerability prediction: a comparative study
Gul Jabeen, Sabit Rahim, Wasif Afzal, et al.
Applied Intelligence (2022) Vol. 52, Iss. 15, pp. 17614-17635
Closed Access | Times Cited: 14
VDoTR: Vulnerability detection based on tensor representation of comprehensive code graphs
Yuanhai Fan, Chuanhao Wan, Cai Fu, et al.
Computers & Security (2023) Vol. 130, pp. 103247-103247
Closed Access | Times Cited: 8
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