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What 41,000 Code Submissions Reveal About Similarity Score Thresholds General 9 min
Priya Sharma Priya Sharma · 2 weeks ago

What 41,000 Code Submissions Reveal About Similarity Score Thresholds

Across 41,000 student submissions at a large public university, an 85% token-level similarity score between two students predicted confirmed misconduct 92% of the time in introductory courses. This guide walks through the exact calibration workflow, score distributions by language, and tiered review thresholds that worked for my assessment team.

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How a CS Professor Spots Refactored Code Plagiarism in Java Labs General 11 min
Dr. Sarah Chen Dr. Sarah Chen · 2 weeks ago

How a CS Professor Spots Refactored Code Plagiarism in Java Labs

This is the workflow Dr. Sarah Chen uses every week to catch plagiarism that survives renaming, reordering, and refactoring. It layers token normalization, AST comparison, and a smart review queue, then walks through what to look for in a diff before talking to a student.

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From Manual Google Searches to Automated Stack Overflow Code Detection General 10 min
Alex Petrov Alex Petrov · 3 weeks ago

From Manual Google Searches to Automated Stack Overflow Code Detection

Quoted Google searches used to be the standard way to catch a Stack Overflow lift. I tracked the shift across tools, fingerprints, and live web corpora, and why modern checks need to pair source matching with AI detection. The short version: the web changed the question from "who copied whom" to "where did this code come from."

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Automating Code Plagiarism Checks in GitHub Actions General 11 min
Emily Watson Emily Watson · 3 weeks ago

Automating Code Plagiarism Checks in GitHub Actions

A practical walkthrough for CS instructors and TAs: wire Codequiry's peer similarity and AI detection into a GitHub Actions workflow, get CSV results on every commit, and triage suspicious submissions in under a minute each.

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AI Code Detector False Positives on Boilerplate General 8 min
Rachel Foster Rachel Foster · 3 weeks ago

AI Code Detector False Positives on Boilerplate

AI code detectors are producing false positives on the most ordinary submissions in CS1: code that looks the same because the assignment required it. This reported piece examines the data, the workflow changes instructors are making, and why combining AI detection with structural similarity reduces the error rate.

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A TA's Method for Refactoring-Resistant Plagiarism Checks General 9 min
James Okafor James Okafor · 4 weeks ago

A TA's Method for Refactoring-Resistant Plagiarism Checks

Line diffs collapse when students rename variables, reorder functions, and extract methods. Here's how token fingerprints and AST normalization catch refactored copies, and how to triage hundreds of similarity reports without drowning in false positives.

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Perplexity Thresholds for Detecting AI Code General 9 min
Alex Petrov Alex Petrov · 4 weeks ago

Perplexity Thresholds for Detecting AI Code

A bootcamp instructor explains how token-level perplexity works as an AI code signal, what thresholds we actually use in Java review, and why a single statistical score is never enough on its own.

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Automating Code Plagiarism Detection in GitHub Actions With Codequiry General 6 min
Rachel Foster Rachel Foster · 4 weeks ago

Automating Code Plagiarism Detection in GitHub Actions With Codequiry

Set up an automated code plagiarism detection pipeline in GitHub Actions using Codequiry's REST API. Follow precise steps to write a workflow YAML and a Python script that submits student code, receives similarity scores, flags suspicious pushes, and optionally detects AI-generated code. Includes threshold tuning, result interpretation, and false positive handling.

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Similarity Score Distributions Across Four Intro CS Languages General 12 min
Priya Sharma Priya Sharma · 1 month ago

Similarity Score Distributions Across Four Intro CS Languages

A three-semester analysis of 4,100 CS1 submissions shows why a 70% similarity score means different things in Python, Java, C++, and JavaScript. I break down percentile thresholds, boilerplate effects, false positives, and how to pair similarity checks with AI detection.

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Detecting Stack Overflow Code in Student Java Submissions General 10 min
Priya Sharma Priya Sharma · 1 month ago

Detecting Stack Overflow Code in Student Java Submissions

Most plagiarism checkers only compare submissions against each other, so a Stack Overflow snippet with renamed variables sails through. We break down how web source matching uses token and AST fingerprints to catch code copied from Stack Overflow, GitHub, and tutorials, and show a Java example where refactoring did not hide the source.

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What 14,000 Python Submissions Reveal About AI Detection Errors General 4 min
Marcus Rodriguez Marcus Rodriguez · 1 month ago

What 14,000 Python Submissions Reveal About AI Detection Errors

A three-semester case study at Briarwood University tracked 14,000 Python assignments through four AI code detectors. The result: false positive rates from 4% to 9% overall, spiking to 23% on common algorithmic patterns. This article breaks down the data, the code patterns that trigger false flags, and a practical workflow for balancing detection with fairness.

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