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AI-Generated Code Detection: The New Frontier in Academic Integrity

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AI-Generated Code Detection: The New Frontier in Academic Integrity

As AI coding assistants become ubiquitous, learn how institutions are adapting to detect AI-generated code and maintain educational standards.

Codequiry Editorial Team · Jan 5, 2026
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How Static Analysis Catches Plagiarized Code Before It Ships General 11 min
Emily Watson · 2 weeks ago

How Static Analysis Catches Plagiarized Code Before It Ships

Plagiarism isn't just a classroom problem. When code from Stack Overflow, GitHub repos, or contractor deliverables enters your production codebase without proper attribution, you risk license violations, IP disputes, and technical debt. This guide shows how static analysis tools detect copied code before it ships, using token matching, AST comparison, and dependency scanning.

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How Winnowing Fingerprints Resist Variable Renaming General 8 min
David Kim · 2 weeks ago

How Winnowing Fingerprints Resist Variable Renaming

Winnowing fingerprinting is a powerful technique for detecting code plagiarism that survives variable renaming, refactoring, and cosmetic changes. This case study examines how the algorithm works, where it succeeds, and where it falls short compared to AST-based approaches.

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How Automatic Grading Evolved From Scripts to Integrity Pipelines General 9 min
Alex Petrov · 2 weeks ago

How Automatic Grading Evolved From Scripts to Integrity Pipelines

A retrospective on automatic grading in computer science education—from shell scripts comparing output strings to modern platforms combining unit tests, static analysis, and code similarity detection. What we gained, what we lost, and why integrity pipelines matter more than ever.

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Building a Source Code Provenance Pipeline for Contractor Deliverables General 10 min
Alex Petrov · 2 weeks ago

Building a Source Code Provenance Pipeline for Contractor Deliverables

When contractors deliver source code, verifying originality and license compliance is critical. This guide walks through building an automated provenance pipeline that checks for code similarity, license violations, and proper attribution before accepting deliverables into your codebase.

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What Code Similarity Metrics Actually Measure in Student Work General 9 min
David Kim · 2 weeks ago

What Code Similarity Metrics Actually Measure in Student Work

Not all code similarity is plagiarism, and not all plagiarism is caught by string matching. This article breaks down the three major detection techniques—AST comparison, token-based analysis, and algorithmic fingerprinting—and explains what each one actually reveals about student submissions.

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An OSPO Lead's Map Through the GNU License Compliance Maze General 12 min
David Kim · 3 weeks ago

An OSPO Lead's Map Through the GNU License Compliance Maze

Navigating the tangled web of GNU license compliance across thousands of repositories isn't an academic exercise—it's a daily operational challenge. This profile of a senior OSPO lead reveals the tools, triage workflows, and legal nuance that keep enterprise products out of litigation.

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How to Build a Source Code Similarity Pipeline for Detection General 12 min
Alex Petrov · 3 weeks ago

How to Build a Source Code Similarity Pipeline for Detection

A step-by-step guide to building a source code similarity detection pipeline from scratch. Covers tokenization, AST comparison, Winnowing fingerprinting, and heuristic scoring. Includes working Python code and configuration strategies used by universities and enterprises.

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What 4,300 JavaScript Projects Reveal About Code Copying General 10 min
James Okafor · 3 weeks ago

What 4,300 JavaScript Projects Reveal About Code Copying

A large-scale study of 4,300 open source JavaScript repositories reveals the true nature of code copying in modern software development. The findings challenge assumptions about originality, attribution, and the tools we use to detect plagiarism.

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Teaching Students to Write Attribution Comments in Group Work General 10 min
David Kim · 3 weeks ago

Teaching Students to Write Attribution Comments in Group Work

Attribution comments are a simple but powerful tool for teaching code integrity in collaborative programming projects. This article explains how to implement them effectively, what to include, and how they transform group work from a plagiarism minefield into a learning opportunity.

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From Paper Traces to Abstract Syntax Trees: Code Similarity Then and Now General 9 min
Rachel Foster · 4 weeks ago

From Paper Traces to Abstract Syntax Trees: Code Similarity Then and Now

The history of code similarity detection is a story of escalating arms races. What started with professors reading printouts has evolved through Unix diffs, token-based fingerprinting, and into modern abstract syntax tree analysis. This retrospective traces the key technical shifts that shaped how we detect code plagiarism in programming courses today.

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Do AST-Based Engines Catch More Refactored Cheating Than Token-Based Ones General 10 min
Dr. Sarah Chen · 4 weeks ago

Do AST-Based Engines Catch More Refactored Cheating Than Token-Based Ones

A mid-sized university CS department ran a controlled study comparing AST-based and token-based plagiarism detection across student assignments that had been systematically refactored. The results reveal which technique handles control flow restructuring, identifier renaming, and method reordering — and where both fail entirely.

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How a TA Spots Refactored Code in 300 Java Submissions General 13 min
Priya Sharma · 1 month ago

How a TA Spots Refactored Code in 300 Java Submissions

Teaching assistants often face the challenge of detecting code plagiarism when students refactor submissions to evade similarity checkers. This article profiles one TA's workflow using AST-based analysis and structural fingerprinting to catch plagiarized code in a large introductory Java course, with practical techniques applicable to any programming educator.

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