Trusted by 500+ Universities Worldwide

Source Code Plagiarism Checking
for Teachers in Computer Science

Catch programming assignment cheating in seconds. Compare student code submissions, detect source code plagiarism from GitHub & Stack Overflow, and generate evidence-ready reports. Powered by Codequiry Hexagram (MOSS v2) for CS educators.

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2-Minute Setup
51+ Languages
FERPA Compliant
Unlimited Checks
500+
Universities Trust Us
10M+
Code Submissions Checked
51+
Programming Languages
99.2%
Detection Accuracy

Everything You Need to Detect Code Plagiarism
in Computer Science Courses

Advanced code similarity detection with Codequiry Hexagram (MOSS v2) technology, designed specifically for educators teaching programming and software development.

Student-to-Student Comparison

Instantly compare all programming assignments against each other. Detect code collusion, shared templates, and collaborative cheating across your entire class. Perfect for catching students who copy each other's homework.

GitHub & Web Source Detection

Scan billions of code repositories including GitHub, GitLab, Bitbucket, Stack Overflow, Chegg, CourseHero, and public assignment solutions. Catch students copying code from online sources.

Anti-Obfuscation Technology

Advanced Codequiry Hexagram (MOSS v2) algorithms detect plagiarism even when students rename variables, reformat code, change comments, or reorder functions. Structural analysis beats simple text matching.

Evidence-Ready Reports

Generate detailed side-by-side diff reports with percentage similarity scores, highlighted matches, and source attribution. Perfect for academic integrity hearings and disciplinary proceedings.

Lightning-Fast Processing

Check 100+ student submissions in under 2 minutes. Batch upload support for ZIP files, drag-and-drop folders, and LMS integration. Get results instantly, not hours later.

51+ Programming Languages

Support for Python, Java, C, C++, JavaScript, TypeScript, Go, Rust, Swift, Kotlin, PHP, Ruby, MATLAB, R, SQL, HTML/CSS, and 35+ more. Automatic language detection included.

AI-Generated Code Detection

Detect code written by ChatGPT, GitHub Copilot, and other AI assistants. Identify unnatural coding patterns and AI-generated structures that students try to pass off as their own work.

Team Access & Collaboration

Add teaching assistants and co-instructors with role-based permissions. Share results securely, add comments, and collaborate on academic integrity investigations.

LMS Integration Ready

Works with Canvas, Blackboard, Moodle, Google Classroom, and other learning management systems. API available for custom integrations and automated workflows.

How Teachers Use Codequiry
to Catch Code Plagiarism

A simple, repeatable workflow that takes minutes to set up and delivers comprehensive plagiarism detection results for every programming assignment.

  1. 1 Upload Student Code Submissions Batch upload ZIP files, drag-and-drop folders, or collect via student portal. Supports individual files or entire project directories.
  2. 2 Run Peer Comparison Check Compare all submissions against each other to detect student-to-student code copying, collusion, and shared templates.
  3. 3 Enable Web & Repository Scanning Scan GitHub, Stack Overflow, and billions of online sources to find where students copied code from the internet.
  4. 4 Review Side-by-Side Results View detailed code diffs with line-level highlighting, similarity percentages, and matched code blocks for easy review.
  5. 5 Export Reports & Take Action Generate PDF reports for academic integrity offices, document violations, and maintain records for compliance.
Read Complete Teacher Guide

Built Specifically for CS Educators

  • Unlimited student comparisons — Check as many submissions as you need without per-check fees
  • Batch processing — Upload entire class submissions at once via ZIP or folder
  • TA & co-instructor access — Add team members with granular permissions
  • FERPA & SOC 2 compliant — Student data protected with enterprise-grade security
  • Private cloud storage — Your submissions never shared or used for training
  • Historical comparison — Check against previous semester submissions
  • Custom filters — Exclude starter code, libraries, and provided templates
  • API access included — Automate workflows and integrate with your tools
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51+ Programming Languages Supported

Detect code plagiarism across every major programming language used in computer science education

Python
Java
C / C++
JavaScript
TypeScript
Go
Rust
Swift
Kotlin
PHP
Ruby
C#
MATLAB
R
SQL
HTML/CSS
Scala
Perl
Lua
Haskell
Assembly
Objective-C
Dart
Julia

Plus 27 more languages with automatic language detection

Trusted by Computer Science Educators Worldwide

See what professors and teachers say about using Codequiry for code plagiarism detection

Codequiry caught 23 cases of plagiarism in my intro CS course that I would have never found manually. The side-by-side comparison and GitHub scanning are game-changers. Much better than MOSS.
Dr. Sarah Chen
Computer Science Professor, Stanford University
The anti-obfuscation technology is incredible. Students were renaming variables and reordering functions, but Codequiry detected the structural similarity instantly. Saved me countless hours of investigation.
Prof. Michael Rodriguez
Associate Professor, MIT CSAIL
Setup took 2 minutes, and I had results for 150 student submissions in under 90 seconds. The batch upload and automatic language detection make this so easy to use. Highly recommend for any CS teacher.
Dr. Jennifer Park
CS Department Chair, UC Berkeley

Why Choose Codequiry Over MOSS or Plagiarism.net?

See how Codequiry compares to traditional code plagiarism detection tools

Feature Codequiry MOSS (Stanford) Plagiarism.net
Student-to-Student Comparison
GitHub & Web Repository Scanning
Anti-Obfuscation Technology Limited
AI-Generated Code Detection
Modern Web Dashboard Basic
Batch Upload Support Email Only
Real-Time Results Hours Wait
API Access Paid Only
Team Collaboration
FERPA Compliant Unclear

Frequently Asked Questions

Common questions from computer science teachers about code plagiarism detection

How accurate is Codequiry at detecting code plagiarism?
Codequiry uses advanced Codequiry Hexagram (MOSS v2) algorithms with structural analysis to achieve 99.2% detection accuracy. Unlike simple text-matching tools, we analyze code structure, logic flow, and algorithmic patterns to detect plagiarism even when students rename variables, reformat code, or change comments. Our anti-obfuscation technology catches sophisticated attempts to disguise copied code.
What programming languages does Codequiry support?
Codequiry supports 51+ programming languages including Python, Java, C, C++, JavaScript, TypeScript, Go, Rust, Swift, Kotlin, PHP, Ruby, C#, MATLAB, R, SQL, HTML/CSS, and many more. We also offer automatic language detection, so you don't need to manually specify the language for each submission.
How is Codequiry different from MOSS (Stanford)?
While MOSS (Measure of Software Similarity) is a pioneering tool, it has limitations: email-only submission, no web interface, no GitHub scanning, hours-long wait times, and no AI detection. Codequiry offers Codequiry Hexagram (MOSS v2) technology with a modern web dashboard, real-time results in under 2 minutes, GitHub/web scanning, AI-generated code detection, batch uploads, API access, and team collaboration features.
Can Codequiry detect AI-generated code from ChatGPT or GitHub Copilot?
Yes! Codequiry includes AI-generated code detection that identifies coding patterns typical of ChatGPT, GitHub Copilot, and other AI assistants. Our machine learning models analyze code structure, comment styles, variable naming patterns, and other signals to flag submissions that may have been AI-generated.
Is my student data secure and FERPA compliant?
Absolutely. Codequiry is FERPA compliant and follows SOC 2 security practices. All student submissions are encrypted at rest and in transit, stored on private cloud infrastructure, and never shared with third parties or used for machine learning training. You maintain full control over your data and can delete it at any time.
How long does it take to check student submissions?
Codequiry delivers results in under 2 minutes for most checks. You can batch upload 100+ student submissions via ZIP file, and our distributed processing infrastructure will compare all submissions and scan web sources simultaneously. Unlike MOSS which can take hours, you get instant results.
Can I integrate Codequiry with my LMS (Canvas, Blackboard, Moodle)?
Yes! Codequiry offers API access and works with Canvas, Blackboard, Moodle, Google Classroom, and other LMS platforms. You can automate submission collection and plagiarism checking workflows. Our API documentation provides integration examples and SDKs for popular languages.
What kind of reports does Codequiry generate?
Codequiry generates comprehensive evidence-ready reports including: side-by-side code diffs with highlighted matches, percentage similarity scores, source attribution (which student or web source code was copied from), matched code blocks with line numbers, and downloadable PDF reports suitable for academic integrity hearings and disciplinary proceedings.

Start Detecting Code Plagiarism Today

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