TAPS: A MOSS Extension for Detecting Software Plagiarism at Scale

Sheahen, D. & Joyner, D. (2016). TAPS: A MOSS Extension for Detecting Software Plagiarism at Scale. In Proceedings of the Third Annual Conference on Learning at Scale. Edinburgh, United Kingdom.

Cheating in computer science classes can damage the reputation of institutions and their students. It is therefore essential to routinely authenticate student submissions with available software plagiarism detection algorithms such as Measure of Software Similarity (MOSS). Scaling this task for large classes where assignments are repeated each semester adds complexity and increases the instructor workload. The MOSS Tool for Addressing Plagiarism at Scale (MOSSTAPS), organizes the MOSS submission task in courses that repeat coding assignments. In a recent use-case in the Online Master of Science in Computer Science (OMSCS) program at the Georgia Institute of Technology, the instructor time spent was reduced from 50 hours to only 10 minutes using the managed submission tool design presented here. MOSS-TAPS provides persistent configuration, supports a mixture of software languages and file organizations, and is implemented in pure Java for cross-platform compatibility.

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