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Building a Source Code Provenance Pipeline for Contractor Deliverables Tutorials 10 min
Alex Petrov Alex Petrov · 2 months 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 David Kim · 2 months 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 David Kim · 2 months 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 Tutorials 12 min
Alex Petrov Alex Petrov · 2 months 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 Pair Programming Looks Like in a Plagiarism Detector General 8 min
Marcus Rodriguez Marcus Rodriguez · 2 months ago

What Pair Programming Looks Like in a Plagiarism Detector

Pair programming and plagiarism can look identical to automated detectors. This article explains the technical signals that distinguish collaborative work from unauthorized code sharing, and how educators can design assignments and detection workflows that respect both academic integrity and modern development practices.

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What 4,300 JavaScript Projects Reveal About Code Copying Case Studies 10 min
James Okafor James Okafor · 2 months 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 Academic Integrity 10 min
David Kim David Kim · 2 months 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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What Open Source Licenses Actually Enforce in Court General 10 min
James Okafor James Okafor · 2 months ago

What Open Source Licenses Actually Enforce in Court

An analysis of 47 open source license enforcement cases from 2008 to 2023 reveals surprising patterns: most violations aren't willful, GPL enforcement rarely goes to trial, and MIT license cases are rising faster than any other. Here's what the data says about what licenses actually enforce in practice versus what developers assume.

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How Cross-Language Code Plagiarism Detection Actually Works General 10 min
Rachel Foster Rachel Foster · 2 months ago

How Cross-Language Code Plagiarism Detection Actually Works

Cross-language code plagiarism presents a growing challenge for programming educators as students discover they can translate solutions between languages to evade detection. This article explains the techniques—AST normalization, semantic fingerprinting, and intermediate representation comparison—that modern tools use to catch these sophisticated cases.

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From Paper Traces to Abstract Syntax Trees: Code Similarity Then and Now General 9 min
Rachel Foster Rachel Foster · 2 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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Do AST-Based Engines Catch More Refactored Cheating Than Token-Based Ones General 10 min
Dr. Sarah Chen Dr. Sarah Chen · 2 months 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 Priya Sharma · 2 months 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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