
MOSS (Measure of Software Similarity)
The industry-standard structural similarity engine for automated code plagiarism detection.

Advanced AI Code Plagiarism Detection and Source Code Integrity Platform.

Codequiry is a high-performance code verification platform specifically engineered to address the complexities of modern software development and academic integrity. In the 2026 landscape, where AI-generated code from models like GPT-5 and Claude 4 is ubiquitous, Codequiry utilizes advanced Abstract Syntax Tree (AST) analysis and proprietary fingerprinting algorithms to distinguish between human-authored logic and synthetic generation. Its technical architecture performs three distinct levels of checks: peer-to-peer comparisons within a local dataset, global database matching against millions of public repositories, and specialized AI-origin detection. The platform supports over 20 programming languages and is built for high-throughput batch processing, making it an essential tool for Computer Science departments and enterprise-level code reviewers. By focusing on structural logic rather than surface-level syntax, Codequiry remains effective against sophisticated code obfuscation techniques and automated refactoring, providing a definitive confidence score for every submission. Its market position is solidified as the primary verification layer for hiring pipelines and legal compliance in software IP management.
Codequiry is a high-performance code verification platform specifically engineered to address the complexities of modern software development and academic integrity.
Explore all tools that specialize in ai code origin detection. This domain focus ensures Codequiry delivers optimized results for this specific requirement.
Explore all tools that specialize in detect code plagiarism. This domain focus ensures Codequiry delivers optimized results for this specific requirement.
Combines AST comparison with logical flow analysis to detect similarity beyond variable renaming.
Analyzes statistical patterns common in LLM-generated code blocks (e.g., ChatGPT, Copilot).
Indexes over 2 billion lines of code from public sources like GitHub, GitLab, and Bitbucket.
Graphical representation of similarity across a large batch of submissions.
Normalizes code into a canonical form before comparison to strip away 'noise' used to trick simple scanners.
Direct plug-and-play modules for Canvas, Moodle, and Blackboard.
Allows users to upload 'Base Code' or 'Template Code' to be excluded from similarity calculations.
Create an account on Codequiry and verify your professional or academic email address.
Access the dashboard and navigate to the 'Projects' section to initiate a new analysis group.
Select the appropriate programming language or 'Auto-detect' for the source files.
Choose the check level: Peer-to-Peer, Global, or AI-Detection (or all three for full coverage).
Upload source files via drag-and-drop or connect a GitHub repository for direct import.
Configure exclusion parameters to ignore common boilerplates or library code (e.g., React imports).
Initiate the 'Full Check' execution and monitor progress through the real-time status bar.
Analyze the generated similarity report, focusing on high-percentage clusters and structural overlaps.
Export detailed findings into PDF or JSON formats for institutional or corporate documentation.
Integrate results into your CI/CD pipeline or LMS via the provided REST API endpoints.
All Set
Ready to go
Verified feedback from other users.
"Highly praised for its ability to catch AI-generated code that other plagiarism checkers miss. Users value the visual reports but note that very small snippets can sometimes trigger false positives."
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The industry-standard structural similarity engine for automated code plagiarism detection.

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