Detecting AI assisted submissions in introductory programming via code anomaly-Reference-Cited by-同舟云学术

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Detecting AI assisted submissions in introductory programming via code anomaly

Published:2024-02-16 Issue: Volume: Page:
ISSN:1360-2357
Container-title:Education and Information Technologies
language:en
Short-container-title:Educ Inf Technol

Author:

Karnalim Oscar^ORCID,Toba Hapnes^ORCID,Johan Meliana Christianti

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10639-024-12520-6.pdf

Reference60 articles.

1. Allen, J.M., Vahid, F., Downey, K., Edgcomb, A.D. (2018). Weekly programs in a cs1 class: experiences with auto-graded many-small programs (msp). Asee annual conference & exposition.

2. Alon, U., Zilberstein, M., & Levy, O. (2019). code2vec: Learning distributed representations of code. ACM on Programming Languages, 3, 1–29.

3. Aurelia, S., Thanuja, R., Chowdhury, S., Hu, Y.C. (2023). Ai-based online proctoring: a review of the state-of-the-art techniques and open challenges. Multimedia Tools and Applications, 1–23

4. Behera, C. K., & Bhaskari, D. L. (2015). Different obfuscation techniques for code protection. Procedia Computer Science, 70, 757–763.

5. Bhattathiripad, P.V. (2012). Software piracy forensics: A proposal for incorporating dead codes and other programming blunders as important evidence in afc test. 2012 ieee 36th annual computer software and applications conference workshops (pp. 206–212)

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