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This paper proposes a method and technology for combining code similarity analysis with the K-means algorithm to achieve a safe, high-level, and plagiarism detection-enabled Online Judge system. The system utilizes Docker containers to effectively prevent malicious code from impacting the system and safeguard the privacy of user-submitted code. By calculating the feature vectors of code to describe its characteristics, the K-means algorithm is employed to cluster these feature vectors for similarity analysis of code blocks. Experimental results demonstrate that the system holds practical application value in enhancing the accuracy and security of code evaluation.

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Design and Implementation of Online Judge System Based on K-means Algorithm for Anti-Plagiarism

  • 会议论文

  • 发表日期：

    2026年

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  • Kaiwei Cen,
  • Yunfei Yi,
  • Yuanyuan Fan

摘要

This paper proposes a method and technology for combining code similarity analysis with the K-means algorithm to achieve a safe, high-level, and plagiarism detection-enabled Online Judge system. The system utilizes Docker containers to effectively prevent malicious code from impacting the system and safeguard the privacy of user-submitted code. By calculating the feature vectors of code to describe its characteristics, the K-means algorithm is employed to cluster these feature vectors for similarity analysis of code blocks. Experimental results demonstrate that the system holds practical application value in enhancing the accuracy and security of code evaluation.