Rachel Foster

General 9 min

Rachel Foster • 4 months 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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General 10 min

Rachel Foster • 4 months ago

Why More CS Departments Are Adopting Layered Detection

Computer science departments are discovering that no single detection method catches every kind of code plagiarism. This article explores the layered detection approach combining structural, web-source, and AI analysis to create a comprehensive academic integrity system.

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General 9 min

Rachel Foster • 4 months ago

What Code Complexity Metrics Miss About Real Maintainability

Cyclomatic complexity, lines of code, and other traditional metrics have been the gold standard for decades — but they systematically miss the factors that actually make code hard to maintain. Here is what experienced teams have learned about measuring what matters.

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General 6 min

Rachel Foster • 5 months ago

The Invisible Theft of Your Website's Core Logic

While everyone watches for stolen CSS and JavaScript, a more insidious theft is happening at the server layer. Our analysis of 500 flagged enterprise codebases reveals that 34% contained verbatim backend logic lifted from competitor sites or leaked repositories. This isn't about aesthetics—it's about stealing business rules, authentication flows, and data models. The tools designed to catch student plagiarism are blind to it.

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Academic Integrity 9 min

Rachel Foster • 5 months ago

Your Students Are Hiding Plagiarism in Plain Sight

Plagiarism detection isn't just about matching code. Savvy students are using sophisticated obfuscation techniques—dead code injection, comment spoofing, and false refactoring—that fool standard similarity checkers. This guide reveals their methods and provides a tactical workflow to uncover the deception, preserving academic integrity in advanced courses.

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General 6 min

Rachel Foster • 5 months ago

Your Static Analysis Tool Is Lying to You About Technical Debt

Cyclomatic complexity and line counts are comforting lies. The technical debt that cripples engineering velocity lives in dependency graphs, commit histories, and the silent consensus of your senior developers. We’re measuring the wrong things and paying for it in missed deadlines and developer burnout.

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Academic Integrity 8 min

Rachel Foster • 5 months ago

The Code Your Students Stole Is Legally Toxic

A student copies a slick React component from a GitHub repo with a strict GPL license. They submit it. They graduate. The original author finds it. Now the university's software IP is contaminated. This isn't just cheating—it's a legal time bomb. We explore the hidden world of license violation through academic plagiarism and how to scan for it before it's too late.

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Academic Integrity 3 min

Rachel Foster • 6 months ago

The Code That Broke a University's Honor Code

A routine data structures assignment at a major university revealed a plagiarism ring involving over 80 students. The fallout wasn't just about cheating—it exposed fundamental flaws in how institutions detect, define, and deter source code copying. This is the story of what broke, and what every CS department needs to fix before the next scandal hits their inbox.

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Case Studies 6 min

Rachel Foster • 6 months ago

The Stanford Professor Who Found 47% AI Code in One Assignment

Professor Aris Thakker’s CS106B assignment looked perfect on the surface. The code compiled, the logic was sound, but something felt deeply off. His investigation, moving beyond traditional similarity checkers, revealed a silent epidemic of AI-generated submissions that threatened to undermine the entire course. This is the story of how one professor learned that in the age of Copilot, plagiarism detection must evolve or become obsolete.

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