Code similarity detectors miss obfuscated or AI-generated submissions in competitive programming, so the author recommends combining automated screening, manual review, and oral interviews.
Curriculum Design of Competitive Programming: a Contest-based Approach
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abstract
Competitive programming (CP) has been increasingly integrated into computer science curricula worldwide due to its efficacy in enhancing students' algorithmic reasoning and problem-solving skills. However, existing CP curriculum designs predominantly employ a problem-based approach, lacking the critical dimension of time pressure of real competitive programming contests. Such constraints are prevalent not only in programming contests but also in various real-world scenarios, including technical interviews, software development sprints, and hackathons. To bridge this gap, we introduce a contest-based approach to curriculum design that explicitly incorporates realistic contest scenarios into formative assessments, simulating authentic competitive programming experiences. This paper details the design and implementation of such a course at Purdue University, structured to systematically develop students' observational skills, algorithmic techniques, and efficient coding and debugging practices. We outline a pedagogical framework comprising cooperative learning strategies, contest-based assessments, and supplemental activities to boost students' problem-solving capabilities.
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The Failure of Plagiarism Detection in Competitive Programming
Code similarity detectors miss obfuscated or AI-generated submissions in competitive programming, so the author recommends combining automated screening, manual review, and oral interviews.