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Detecting copied boilerplate vs real plagiarism
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The literature on detecting copied boilerplate vs real plagiarism is about accuracy. The people doing it spend their time on filing, sequencing, and what to say to someone who disagrees.
Deciding what the output is for
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Self-plagiarism and legitimate reuse need separate handling, and a similarity score cannot tell them apart. A student reusing their own prior submission, a developer reusing a snippet from an internal library and an author lifting a file from a public repository can all produce the same number. Only provenance separates them, so provenance has to be captured at the moment of the match rather than reconstructed later.
What the reviewer actually needs
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The expensive failure is not a missed match, it is an unexplainable one. A missed match costs you a case you never knew about; an unexplainable one costs an afternoon, a complaint, and a permanent reduction in how much anyone trusts the next result. Optimising recall while leaving the explanation thin trades a cheap failure for an expensive one, which is exactly backwards.
Making it survive the year
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Run it on the first assignment of the term, not the last. Finding reuse in week two changes what the student does for the rest of the course; finding it in week twelve changes only what goes on a form. The detection quality is identical in both cases and the outcome is not remotely comparable, which makes timing the highest-leverage variable in the whole exercise and the one least often discussed.
Putting it into practice
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The right time to set up a Codequiry is before the term that needs it, not during.
Reference: https://codequiry.com