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Does Convergent AI Output Look Like Peer Plagiarism to a Detector? General 10 min
James Okafor James Okafor · 1 month ago

Does Convergent AI Output Look Like Peer Plagiarism to a Detector?

Twenty-three of 412 submissions in a data structures course shared a Dijkstra implementation that differed by fewer than three tokens, and the peer similarity engine flagged all 23 as a single cluster. Nobody had copied anybody. Here is the mechanism behind convergent AI output, the identifiers and AST evidence that separated it from real collusion, and the three-pass workflow we used to keep the scores from contaminating each other.

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What Cross-Language Code Plagiarism Detection Can and Cannot See General 11 min
James Okafor James Okafor · 1 month ago

What Cross-Language Code Plagiarism Detection Can and Cannot See

Cross-language code plagiarism detection compares normalized structure rather than raw text, which works when a translation was mechanical and fails when the student rewrote the algorithm. Here is what survives a Java-to-Python translation, what the token and IR approaches actually see, and how to run the check across a whole cohort without drowning in false positives.

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What One CS Department Learned From a Year of AI Code Detection General 11 min
Priya Sharma Priya Sharma · 1 month ago

What One CS Department Learned From a Year of AI Code Detection

A public research university ran AI code detection as part of its grading workflow for a full academic year: eleven assignments, three courses, 4,118 submissions. The interesting number isn't the 3.8% that ended in a finding. It's the roughly two flagged files that got cleared for every one that held up, and what the department changed because of it.

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How Cross-Language Code Plagiarism Detection Works General 13 min
Alex Petrov Alex Petrov · 1 month ago

How Cross-Language Code Plagiarism Detection Works

A Java submission and a Python submission looked nothing alike, but they were the same algorithm translated line by line. This is the story of how cross-language code plagiarism detection actually works, where it catches translated code, and where it still fails.

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Interpreting Code Similarity Scores in Programming Courses General 9 min
Priya Sharma Priya Sharma · 1 month ago

Interpreting Code Similarity Scores in Programming Courses

Similarity scores are ranking signals, not verdicts. I'll walk through the distributions, thresholds, and triage rules I use when reviewing code similarity reports for 400-student courses, plus where AI-generated code fits in the same queue.

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Designing Coding Assignments That AI Can't One-Shot General 10 min
Alex Petrov Alex Petrov · 1 month ago

Designing Coding Assignments That AI Can't One-Shot

As a bootcamp instructor, I've graded hundreds of take-home coding challenges. The AI-resistant ones share a pattern: they ask for process artifacts, not just final code. Here's how to design assignments that hold up.

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The Long Road to Refactoring-Resistant Code Plagiarism Detection General 6 min
Alex Petrov Alex Petrov · 1 month ago

The Long Road to Refactoring-Resistant Code Plagiarism Detection

A hands-on retrospective on how code similarity detection grew from naive line diffs to tokenization, ASTs, and fingerprinting. Follow a step-by-step Python prototype and a production workflow with Codequiry to catch refactored plagiarism in CS courses.

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A Short History of AI-Generated Code Detection General 8 min
Dr. Sarah Chen Dr. Sarah Chen · 1 month ago

A Short History of AI-Generated Code Detection

A CS professor traces how AI-generated code detection grew out of MOSS-era token fingerprints, code stylometry, and a broken similarity assumption. The piece explains how modern detectors work, where they still stumble, and why stacked peer, web, and AI signals make the most defensible academic workflow.

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A TA's Script for Sorting 300 Code Similarity Reports by Office Hours General 8 min
Rachel Foster Rachel Foster · 1 month ago

A TA's Script for Sorting 300 Code Similarity Reports by Office Hours

A teaching assistant at UC San Diego reduced a 312-submission similarity queue to a shortlist of 14 files in about two hours. The workflow relies on Codequiry's outlier scoring, a Python triage script, and a strict two-pass review rule. Here is the exact process, including the script and the thresholds she uses.

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How Open Source License Scanning Evolved From SPDX to Policy Gates General 7 min
David Kim David Kim · 1 month ago

How Open Source License Scanning Evolved From SPDX to Policy Gates

License scanning went from hand-checking COPYING files to SPDX metadata and policy-as-code gates. This piece traces that arc, shows which gaps still let copied code slip through, and explains how to pair license scans with source matching for audit-grade evidence.

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