Výsledky vyhľadávania - Artificial Intelligence Generated Code Detection

AIGCodeSet: A New Annotated Dataset for AI Generated Code Detection

Autori: Demirok, Basak Kutlu, Mucahid

Zdroj: 2025 33rd Signal Processing and Communications Applications Conference (SIU). :1-4

Predmety: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence

Prístupová URL adresa: http://arxiv.org/abs/2412.16594

AI-Generated Code Detection: An Examination of Current Tools in Education

Autori: Juan Esteban Cuellar Argotty Ruben Manrique

Zdroj: Lecture Notes in Computer Science ISBN: 9783031982804

LevDetectCode: Zero-Shot Detection of AI-Generated Code Using Levenshtein Distance.

Autori: Fu, Jiazhou Shen, Guohua Huang, Zhiqiu a ďalší

Zdroj: International Journal of Software Engineering & Knowledge Engineering. Dec2025, Vol. 35 Issue 12, p1713-1736. 24p.

Predmety: CODE generators, DETECTION algorithms, SIGNAL detection, COMPUTER performance

MultiAIGCD: A Comprehensive dataset for AI Generated Code Detection Covering Multiple Languages, Models,Prompts, and Scenarios

Autori: Demirok, Basak Kutlu, Mucahid Mergen, Selin

Predmety: Software Engineering (cs.SE), FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Software Engineering

Prístupová URL adresa: http://arxiv.org/abs/2507.21693

$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection

Autori: Orel, Daniil Paul, Indraneil Gurevych, Iryna a ďalší

Predmety: Software Engineering (cs.SE), FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computers and Society (cs.CY), Software Engineering, Computers and Society

Prístupová URL adresa: http://arxiv.org/abs/2507.10583

Hiding in Plain Sight: On the Robustness of AI-Generated Code Detection

Autori: Saman Pordanesh Sufiyan Bukhari Benjamin Tan a ďalší

Zdroj: Lecture Notes in Computer Science ISBN: 9783031976223

Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education

Autori: Wei Hung Pan Ming Jie Chok Jonathan Leong Shan Wong a ďalší

Zdroj: Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training. :1-11

Predmety: Computer Science - Software Engineering, Artificial Intelligence and Robotics, Computer Science - Artificial Intelligence, Software Engineering Education, Software Engineering, AI-Generated Code Detection, AI-Generated Code

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2401.03676

AI-Generated Code Detection and Quality/Security Assessment Framework

Autori: Saiyad Uzaib

Zdroj: International Journal of Multidisciplinary and Scientific Emerging Research. 13

Security Analysis of Automated Code Generation: Structural Vulnerabilities in AI-Generated Code.

Autori: Yoo, Sang Hyun Kim, Hyun Jung

Zdroj: Technical Journal / Tehnički Glasnik; Dec2025, Vol. 19 Issue 4, p560-574, 15p

Predmety: COMPUTER security vulnerabilities, COMPUTER software security, CODE generators, SOFTWARE verification, RISK assessment

CDUP: Detecting AI Generated Code Using Abstract Syntax Tree Analyst.

Autori: Păuleț, Ștefan Moruz, Alex

Zdroj: Procedia Computer Science. 2025, Vol. 270, p2088-2095. 8p.

Predmety: Plagiarism prevention, C (Computer program language), Data analytics, Hypothesis, Code generators, Data structures

Exploring the Boundaries Between LLM Code Clone Detection and Code Similarity Assessment on Human and AI-Generated Code

Autori: Zixian Zhang Takfarinas Saber

Zdroj: Big Data and Cognitive Computing, Vol 9, Iss 2, p 41 (2025)

Predmety: code clone detection, code similarity, large language model, fine-tuning, LLM-generated code, Technology

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2504-2289/9/2/41; https://doaj.org/toc/2504-2289

Prístupová URL adresa: https://doaj.org/article/1de3cfaf5b7d4fb6ba7f9a4dee7fb25c

Using pseudo-AI submissions for detecting AI-generated code

Autori: Shariq Bashir

Zdroj: Frontiers in Computer Science, Vol 7 (2025)

Predmety: programming code plagiarism detection, detecting AI-generated code, generative AI tools, large language models (LLMs), programming code similarity, Electronic computers. Computer science, QA75.5-76.95

Popis súboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fcomp.2025.1549761/full; https://doaj.org/toc/2624-9898

Prístupová URL adresa: https://doaj.org/article/5eca89389855411a842764250235718c

AIGCodeSet: A New Annotated Dataset for AI Generated Code Detection

Autori: Demirok, Basak Kutlu, Mucahid

Témy: Computer Science - Software Engineering, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2412.16594

An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far are We?

Autori: Hyunjae Suh Mahan Tafreshipour Jiawei Li a ďalší

Zdroj: 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE). :859-871

Predmety: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering

Prístupová URL adresa: http://arxiv.org/abs/2411.04299

Security Analysis of Automated Code Generation: Structural Vulnerabilities in AI-Generated Code

Autori: Sang Hyun Yoo Hyun Jung Kim

Zdroj: Tehnički Glasnik, Vol 19, Iss 4, Pp 560-574 (2025)

Predmety: AI-generated code, binary analysis, encryption vulnerabilities, LLM security, memory vulnerabilities, OWASP Top 10, Technology

Popis súboru: electronic resource

Relation: https://hrcak.srce.hr/file/484966; https://doaj.org/toc/1846-6168; https://doaj.org/toc/1848-5588

Prístupová URL adresa: https://doaj.org/article/376290d6794d42a3acce1cf7b92db307

Exploring the Boundaries Between LLM Code Clone Detection and Code Similarity Assessment on Human and AI-Generated Code.

Autori: Zhang, Zixian Saber, Takfarinas

Zdroj: Big Data & Cognitive Computing; Feb2025, Vol. 9 Issue 2, p41, 19p

Predmety: LANGUAGE models, HUMAN cloning, SEMANTICS

Detection of Malicious Codes Generated by Large Language Models: A Comparison of GPT-3.5, GPT-4o, Gemini, and Claude.

Autori: Pehlivanoğlu, Meltem Kurt Çoban, Murat Görkem

Zdroj: International Journal of Information Security Science. 2025, Vol. 14 Issue 1, p1-12. 12p.

Predmety: *LANGUAGE models, *MACHINE learning, *ARTIFICIAL intelligence, *GENERATIVE pre-trained transformers, *RANDOM forest algorithms

Assessing AI detectors in identifying AI-generated code: Implications for education

Autori: PAN, Wei Hung CHOK, Ming Jie WONG, Jonathan Leong Shan a ďalší

Zdroj: Research Collection School Of Computing and Information Systems

Predmety: Software Engineering Education, AI-Generated Code, AI-Generated Code Detection, Artificial Intelligence and Robotics, Software Engineering

Popis súboru: application/pdf

Relation: https://ink.library.smu.edu.sg/sis_research/9244; https://ink.library.smu.edu.sg/context/sis_research/article/10244/viewcontent/3639474.3640068.pdf

Dostupnosť: https://ink.library.smu.edu.sg/sis_research/9244
https://ink.library.smu.edu.sg/context/sis_research/article/10244/viewcontent/3639474.3640068.pdf

Using pseudo-AI submissions for detecting AI-generated code.

Autori: Bashir, Shariq

Zdroj: Frontiers in Computer Science; 2025, p1-11, 11p

An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far Are We?

Autori: Suh, Hyunjae Tafreshipour, Mahan Li, Jiawei a ďalší

Témy: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2411.04299