Code Intelligence Hub

General 7 min

Priya Sharma · 4 weeks ago

Inside UT Austin's Refactoring-Resistant Code Similarity Pipeline

When the University of Texas at Austin’s CS 312 course saw a spike in suspicious submissions that evaded their existing checks, they turned to token-based similarity analysis to catch code that had been renamed, reorganized, and logic-swapped. This case study walks through the techniques, the results, and the lessons for any institution facing refactoring-resistant plagiarism.

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General 8 min

Rachel Foster · 4 weeks ago

Inside a Startup’s Codebase License Compliance Audit

When a fintech startup faced a pre-funding due diligence request, they discovered copies of GPL-licensed libraries scattered across their proprietary codebase. This case study follows their eight-week audit, blending automated scanning tools like Codequiry and FOSSology with manual triage to achieve compliance without derailing their development roadmap.

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General 10 min

Priya Sharma · 4 weeks ago

The Long Road to Refactoring-Resistant Code Plagiarism Detection

Code refactoring — renaming variables, reordering statements, extracting functions — has long been the easiest way for students to disguise copied code. This article traces the thirty-year arms race between obfuscation tactics and detection techniques, from simple string comparison to modern AST and graph-based analysis that can spot similarities even after heavy transformation. Understanding this history explains why no single method is perfect and how layered approaches like Codequiry’s hybrid engine achieve the highest accuracy.

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General 8 min

James Okafor · 1 month ago

How Code Similarity Detection Advanced From Strings to Semantics

From manual diff checks to AI-powered semantic analysis, code plagiarism detection has undergone a fundamental transformation. This article traces the key milestones—MOSS, JPlag, AST fingerprinting, and the new frontier of LLM-written code—and explains why a single method is no longer enough.

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General 10 min

Alex Petrov · 1 month ago

How Much Copied Stack Overflow Code Do Plagiarism Tools Actually Catch

Traditional similarity tools like MOSS and JPlag compare student submissions against each other but leave a massive blind spot: code copied directly from Stack Overflow, GitHub repositories, and online tutorials. This article examines how web source detection works, what it catches that peer comparison misses, and why both approaches together give you the real picture of code originality.

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Academic Integrity 11 min

Emily Watson · 1 month ago

Teaching Code Attribution Before Students Write a Single Line

Too many CS students treat code from Stack Overflow, GitHub, or AI tools as free for the taking. Teaching attribution as a core skill from the first assignment reduces plagiarism and builds professional habits. This article walks through concrete strategies, assignment patterns, and detection workflows that make attribution part of the learning process.

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AI Detection 9 min

Priya Sharma · 1 month ago

How Burstiness and Perplexity Catch AI-Generated Code

Burstiness and perplexity aren't just linguistic curiosities—they're the primary statistical signals that distinguish human-written source code from LLM output. This article explains exactly how these measures work under the hood, with worked examples, real-world detection rates, and honest limitations.

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Case Studies 2 min

David Kim · 1 month ago

One Community College's Web Code Plagiarism Strategy

When intro programming students at a mid-sized community college were copying entire code snippets from Stack Overflow and GitHub, the department needed a scalable detection solution. By integrating Codequiry’s web-source matching into their grading pipeline, they reduced surface-level copy-paste incidents by 40% in a single semester while cutting manual review time by 60%.

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Case Studies 9 min

Emily Watson · 1 month ago

What 1200 Python CS1 Submissions Reveal About AI-Written Code Signatures

We analyzed 1200 introductory Python submissions from three semesters, applying perplexity, burstiness, and token-frequency analysis to separate human-written code from AI-generated samples. The results reveal a consistent set of statistical signatures that can catch GPT-generated and Copilot-assisted assignments—with measured false-positive rates at each threshold.

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General 9 min

Alex Petrov · 1 month ago

How Code Similarity Checks Catch Open Source License Violations

Code similarity analysis isn't just for catching student plagiarism. Organizations use the same techniques to identify GPL and other open source license violations in their proprietary codebases. This article walks through the algorithms, real-world cases, and practical workflows for automated license compliance auditing.

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General 8 min

James Okafor · 1 month ago

Cross-Language Code Plagiarism Detection Methods Tested

A rigorous head-to-head comparison of three cross-language code plagiarism detection approaches—tokenization, AST matching, and semantic fingerprinting—tested on 100 student-style assignments translated between Java, Python, and C++. We reveal which method catches translated loops, renamed variables, and switched control flow, and which one drowns in false positives.

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Tutorials 8 min

Emily Watson · 1 month ago

Automating Code Plagiarism Detection in Your Grading Workflow

A practical walkthrough for CS instructors who want to wire code similarity checks directly into their grading workflow. Covers tooling choices, LMS integration, and how to layer in web-source and AI-generated code detection for a complete academic integrity pipeline.

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