Automated assessment in computer science education: A state-of-the-art review

JC Paiva, JP Leal, Á Figueira - ACM Transactions on Computing …, 2022 - dl.acm.org
Practical programming competencies are critical to the success in computer science (CS)
education and go-to-market of fresh graduates. Acquiring the required level of skills is a long …

Cyber security threats detection in internet of things using deep learning approach

F Ullah, H Naeem, S Jabbar, S Khalid, MA Latif… - IEEE …, 2019 - ieeexplore.ieee.org
The IoT (Internet of Things) connect systems, applications, data storage, and services that
may be a new gateway for cyber-attacks as they continuously offer services in the …

Dgcnn: A convolutional neural network over large-scale labeled graphs

AV Phan, M Le Nguyen, YLH Nguyen, LT Bui - Neural Networks, 2018 - Elsevier
Exploiting graph-structured data has many real applications in domains including natural
language semantics, programming language processing, and malware analysis. A variety of …

Convolutional neural networks over control flow graphs for software defect prediction

AV Phan, M Le Nguyen, LT Bui - 2017 IEEE 29th International …, 2017 - ieeexplore.ieee.org
Existing defects in software components is unavoidable and leads to not only a waste of time
and money but also many serious consequences. To build predictive models, previous …

A comparison of code similarity analysers

C Ragkhitwetsagul, J Krinke, D Clark - Empirical Software Engineering, 2018 - Springer
Copying and pasting of source code is a common activity in software engineering. Often, the
code is not copied as it is and it may be modified for various purposes; eg refactoring, bug …

ModelDiff: Testing-based DNN similarity comparison for model reuse detection

Y Li, Z Zhang, B Liu, Z Yang, Y Liu - Proceedings of the 30th ACM …, 2021 - dl.acm.org
The knowledge of a deep learning model may be transferred to a student model, leading to
intellectual property infringement or vulnerability propagation. Detecting such knowledge …

Unleashing the hidden power of compiler optimization on binary code difference: An empirical study

X Ren, M Ho, J Ming, Y Lei, L Li - Proceedings of the 42nd ACM …, 2021 - dl.acm.org
Hunting binary code difference without source code (ie, binary diffing) has compelling
applications in software security. Due to the high variability of binary code, existing solutions …

Definition, approaches, and analysis of code duplication detection (2006–2020): a critical review

CF Chen, AM Zain, KQ Zhou - Neural Computing and Applications, 2022 - Springer
Code duplication detection is the act of finding similar code in software development. It is
important for software engineer to address the issues of code duplication detection. In this …

Detecting automatic software plagiarism via token sequence normalization

T Sağlam, M Brödel, L Schmid, S Hahner - Proceedings of the IEEE …, 2024 - dl.acm.org
While software plagiarism detectors have been used for decades, the assumption that
evading detection requires programming proficiency is challenged by the emergence of …

Academic source code plagiarism detection by measuring program behavioral similarity

H Cheers, Y Lin, SP Smith - IEEE Access, 2021 - ieeexplore.ieee.org
Source code plagiarism is a long-standing issue in tertiary computer science education.
Many source code plagiarism detection tools have been proposed to aid in the detection of …