New Breakthrough AI Detection. Our best yet for AI-written source code. Catches 90% of AI/GPT code with 1.3% false flags. 90% caught, 1.3% false flags. Read more Read more
New: MCP integration. Run plagiarism scans from Claude, Cursor or any AI assistant. Run scans from Claude or Cursor. Set it up

Code Intelligence Hub

Expert insights on AI code detection and academic integrity

All Code Plagiarism AI Detection Academic Integrity Web Plagiarism Code Quality Open Source Licensing Tutorials Case Studies

Latest Articles

Stay ahead with expert analysis and practical guides

A TA's Script for Sorting 300 Code Similarity Reports by Office Hours General 8 min
Rachel Foster Rachel Foster · 3 weeks 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.

Read →
How Open Source License Scanning Evolved From SPDX to Policy Gates General 7 min
David Kim David Kim · 3 weeks 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.

Read →
How Code Plagiarism Detection Algorithms Ignore Renamed Variables General 9 min
Marcus Rodriguez Marcus Rodriguez · 4 weeks ago

How Code Plagiarism Detection Algorithms Ignore Renamed Variables

A student renames every variable and converts for loops to while loops. MOSS still flags 94%. This guide builds a minimal winnowing detector in Python 3.11 so you can see exactly why code plagiarism detection algorithms survive refactoring. We then look at where the approach breaks and how AST matching fills the gap.

Read →
Why a 400-Student Intro Course Adopted Layered Code Checks General 11 min
Dr. Sarah Chen Dr. Sarah Chen · 4 weeks ago

Why a 400-Student Intro Course Adopted Layered Code Checks

One CS department's switch from a single similarity tool to a layered detection workflow changed what they could see in student code. Peer copying, web sources, and AI-generated submissions each required different signals, and combining them revealed more than any one check alone.

Read →
How to Detect Code Copied From Online Sources in Student Submissions General 9 min
Alex Petrov Alex Petrov · 1 month ago

How to Detect Code Copied From Online Sources in Student Submissions

A bootcamp instructor walks through the exact workflow he uses to catch student code copied from tutorials, GitHub repos, and Stack Overflow answers, including what peer-only checkers miss, how to read web match reports without false positives, and where Codequiry fits.

Read →
Scanning 9,301 Python Files for Stack Overflow Copy-Paste General 10 min
James Okafor James Okafor · 1 month ago

Scanning 9,301 Python Files for Stack Overflow Copy-Paste

A practical, code-level guide to batch-scanning Python files for web-sourced code. We walk through token normalization, fingerprinting, uploading to Codequiry, interpreting web match URLs, and stacking an AI check on flagged files. Built for CS professors auditing assignments and engineering managers verifying contractor code.

Read →
AI Code Detector Comparison Across Codequiry, GPTZero, and Copyleaks General 10 min
Dr. Sarah Chen Dr. Sarah Chen · 1 month ago

AI Code Detector Comparison Across Codequiry, GPTZero, and Copyleaks

A CS professor ran 1,200 Java submissions through three AI code detectors. Codequiry caught 94% of known AI files and flagged only 3.5% of pre-LLM human code, while the other tools posted two to three times that false positive rate. The full numbers and methods are below.

Read →
What 41,000 Code Submissions Reveal About Similarity Score Thresholds General 9 min
Priya Sharma Priya Sharma · 1 month 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.

Read →
Web Code Plagiarism Detection Through Source Fingerprinting General 11 min
Marcus Rodriguez Marcus Rodriguez · 1 month ago

Web Code Plagiarism Detection Through Source Fingerprinting

Peer-based plagiarism checkers miss code copied from GitHub and Stack Overflow. This analysis walks through how web source fingerprinting works, what a 214-submission Java audit found, and where the approach breaks down. Includes a method comparison table and a practical review workflow.

Read →