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For decades many computing departments have deployed systems for the detection of plagiarised student source code submissions. Automated systems to detect free-text student plagiarism are just becoming available and the experience of computing educators is valuable for their successful deployment.This paper describes a Four-Stage Plagiarism Detection Process that attempts to ensure no suspicious similarity is missed and that no student is unfairly accused of plagiarism. Required characteristics of an effective similarity detection engine are proposed and an investigation of a simple engine is described. An innovative prototype tool designed to decrease the workload of tutors investigating undue similarity is also presented.
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Stored only when both papers are in the corpus — 24 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.