TAPS: A MOSS Extension for Detecting Software Plagiarism at Scale

Abstract

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.

Full Paper

The full paper “TAPS: A MOSS Extension for Detecting Software Plagiarism at Scale” can be found here.

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  • 25 Apr 2016: David, Dana, and Chaohua present at Learning @ Scale 2016. David Joyner, Dana Sheahen, and Chaohua Ou are in Edinburgh, Scotland presenting our five papers. All five presentations are part of the conference's flipped sessions, and the pre-recorded presentations are available here.
  • 15 Apr 2016: Learning @ Scale Flipped Presentations Now Available. For our five Learning @ Scale papers, we are participating in a flipped session. This entails filming the presentation in advance. The presentations are open to the public and now available.
  • 10 Feb 2016: Fifth Paper Accepted to Learning @ Scale 2016. "TAPS: A MOSS Extension for Detecting Software Plagiarism at Scale", co-authored by Dana Sheahen and David Joyner, has been accepted as a short paper to Learning @ Scale 2016. Congratulations, Dana and David!