Search Results - AI Generated Code Detection

Using pseudo-AI submissions for detecting AI-generated code by Bashir, Shariq

“… Students may use these tools inappropriately for their programming assignments, and there currently are not reliable methods to detect AI-generated code…”
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CDUP: Detecting AI Generated Code Using Abstract Syntax Tree Analyst by Păuleț, Ștefan, Moruz, Alex

“… Most work in the field is aimed at the larger problem of detecting AI generated text, leaving an important gap as far as specialized tools for code detection are concerned…”
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AI Generated Code Plagiarism Detection in Computer Science Courses: A Literature Mapping by Simmons, Archer, Holanda, Maristela, Chamon, Christiana, Da Silva, Dilma

“…, methods of plagiarism have evolved, however methods of detection may not be capable of accurately differentiating between code generated by human and artificial intelligence (AI…”
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Exploring the Boundaries Between LLM Code Clone Detection and Code Similarity Assessment on Human and AI-Generated Code by Zhang, Zixian, Saber, Takfarinas

“…As Large Language Models (LLMs) continue to advance, their capabilities in code clone detection have garnered significant attention…”
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Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education by Pan, Wei Hung, Chok, Ming Jie, Wong, Jonathan Leong Shan, Shin, Yung Xin, Poon, Yeong Shian, Yang, Zhou, Chong, Chun Yong, Lo, David, Lim, Mei Kuan

“…Educators are increasingly concerned about the usage of Large Language Models (LLMs) such as ChatGPT in programming education, particularly regarding the potential exploitation of imperfections in Artificial Intelligence Generated Content…”
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An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far are We? by Suh, Hyunjae, Tafreshipour, Mahan, Li, Jiawei, Bhattiprolu, Adithya, Ahmed, Iftekhar

“… This study first presents an empirical analysis to investigate the effectiveness of the existing AI detection tools in detecting AI-generated code…”
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AIGCodeSet: A New Annotated Dataset for AI Generated Code Detection by Demirok, Basak, Kutlu, Mucahid

“… Therefore, determining whether a piece of code is written by a human or generated by an artificial intelligence (AI…”
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AIGCodeSet: A New Annotated Dataset for AI Generated Code Detection by Basak Demirok, Kutlu, Mucahid

“… In this study, we introduce AIGCodeSet, a dataset for AI-generated code detection tasks, specifically for the Python programming language…”
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Detecting Adversarial Prompted AI-Generated Code on Stack Overflow: A Benchmark Dataset and an Enhanced Detection Approach by Swaraj, Aman, Agarwal, Krishna, Joshi, Atharv, Kumar, Sandeep

“… While recent studies have focused on detecting AI-generated code, they have mostly worked with long code samples from repositories and assignments…”
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Detecting AI-Generated Source Code in Student Assignments Using Steganographic Watermarks by Horvath, Marek, Bubenkova, Lenka, Pietrikova, Emilia, Corba, Matej

“… The system helps detect plagiarism and the use of AI models without altering visible content or functionality…”
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DeVAIC: A tool for security assessment of AI-generated code by Cotroneo, Domenico, De Luca, Roberta, Liguori, Pietro

“… This research work introduces DeVAIC (Detection of Vulnerabilities in AI-generated Code), a tool to evaluate the security of AI-generated Python code, which overcomes the challenge of examining incomplete code…”
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An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far Are We? by Suh, Hyunjae, Mahan Tafreshipour, Li, Jiawei, Bhattiprolu, Adithya, Ahmed, Iftekhar

“… This study first presents an empirical analysis to investigate the effectiveness of the existing AI detection tools in detecting AI-generated code…”
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Security Analysis of Automated Code Generation: Structural Vulnerabilities in AI-Generated Code by Yoo, Sang Hyun, Kim, Hyun Jung

“… This study examines the susceptibilities inherent in AI-generated code through a hybrid methodology that combines Ghidra for static analysis with Valgrind and Frida for dynamic evaluation to identify…”
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Security Analysis of Automated Code Generation: Structural Vulnerabilities in AI-Generated by Kim, Hyun Jung, Yoo, Sang Hyun

“… This study examines the susceptibilities inherent in AI-generated code through a hybrid methodology that combines Ghidra for static analysis with Valgrind and Frida for dynamic evaluation to identify…”
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Artifact feature purification for cross-domain detection of AI-generated images by Meng, Zheling, Peng, Bo, Dong, Jing, Tan, Tieniu, Cheng, Haonan

“… Existing generated image detection methods suffer from performance drops when faced with out-of-domain generators and image scenes…”
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Generative AI for thematic analysis in a maternal health study: coding semistructured interviews using large language models by Qiao, Shan, Fang, Xingyu, Wang, Junbo, Zhang, Ran, Li, Xiaoming, Kang, Yuhao

“…: Using transcripts from interviews conducted with maternity care providers in South Carolina, we leveraged ChatGPT for inductive coding to generate codes from interview transcripts without a predetermined coding scheme…”
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Is This You, LLM? Recognizing AI-written Programs with Multilingual Code Stylometry by Gurioli, Andrea, Gabbrielli, Maurizio, Zacchiroli, Stefano

“…With the increasing popularity of LLM-based code completers, like GitHub Copilot, the interest in automatically detecting AI-generated code is also increasing-in particular in contexts where the use…”
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Evaluating ChatGPT-3’s efficacy in solving coding tasks: implications for academic integrity in English language assessments by Elhambakhsh, Seyedeh Elham

“… The researcher explored potential implications for academic integrity and the challenges associated with AI-generated solutions…”
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Closing the Gap: A User Study on the Real-world Usefulness of AI-powered Vulnerability Detection & Repair in the IDE by Steenhoek, Benjamin, Sivaraman, Kalpathy, Gonzalez, Renata Saldivar, Mohylevskyy, Yevhen, Moghaddam, Roshanak Zilouchian, Le, Wei

“…Security vulnerabilities impose significant costs on users and organizations. Detecting and addressing these vulnerabilities early is crucial to avoid exploits and reduce development costs…”
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GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPT by Nguyen, Phuong T., Di Rocco, Juri, Di Sipio, Claudio, Rubei, Riccardo, Di Ruscio, Davide, Di Penta, Massimiliano

“…, in software education) rather than as a replacement for humans. Thus, detecting automatically generated source code by ChatGPT is necessary, and tools for identifying AI-generated content need to be adapted to work effectively with code…”
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