Detect plagiarized and similar code across trillions of code sources on the web See what's new
Dr. Sarah Chen

Dr. Sarah Chen

AI Detection Researcher at Codequiry

Sarah leads AI-generated code research at Codequiry, focusing on how large-language-model output can be reliably distinguished from human-written code.

Articles by Dr. Sarah Chen

What Happens When a CS Course Runs Both MOSS and ChatGPT Detectors General 11 min
Dr. Sarah Chen Dr. Sarah Chen 1 week ago

What Happens When a CS Course Runs Both MOSS and ChatGPT Detectors

Over 1,200 student submissions from a large public university’s introductory Python course were analyzed with Codequiry’s similarity engine and its AI code detector. The results show how traditional plagiarism tools miss a growing fraction of unauthorized work—and why layering AI detection changes what instructors actually see.

Writing Programming Assignments That Resist Plagiarism General 7 min
Dr. Sarah Chen Dr. Sarah Chen 1 week ago

Writing Programming Assignments That Resist Plagiarism

We cut similarity rates from 43% to 7% in a Data Structures course not by policing harder but by rewriting the assignments themselves. Here's what worked, what broke, and where detection tools like Codequiry still earn their keep.

How AST-Based Similarity Catches Disguised Code Plagiarism General 15 min
Dr. Sarah Chen Dr. Sarah Chen 3 weeks ago

How AST-Based Similarity Catches Disguised Code Plagiarism

Token-based plagiarism detectors match sequences of tokens, but smart students can evade them by renaming variables, reordering statements, and refactoring code. Abstract Syntax Tree (AST) comparison digs deeper into the structural DNA of a program, making it far harder to disguise copied code. Learn how AST-based detection works, why it catches what MOSS and JPlag miss, and where Codequiry’s multi-layered approach fits in.

Why CS Departments Are Now Running AI Checks After Plagiarism General 12 min
Dr. Sarah Chen Dr. Sarah Chen 3 weeks ago

Why CS Departments Are Now Running AI Checks After Plagiarism

When Midwestern State University’s CS department discovered that MOSS alone missed nearly a third of suspicious submissions—many generated by ChatGPT—they implemented a two-stage detection pipeline. This is what they learned about running plagiarism checks first, then AI detection, and why the combination caught more than either tool alone.

Designing Plagiarism-Resistant Programming Assignments General 11 min
Dr. Sarah Chen Dr. Sarah Chen 1 month ago

Designing Plagiarism-Resistant Programming Assignments

Copy-paste code and AI-generated solutions are flooding CS courses. Smart assignment design—parameterized prompts, incremental checkpoints, and open-ended specs—can make copying so cumbersome that students default to doing their own work. This deep dive builds a concrete, reusable playbook for instructors.

Why Some CS Departments Are Moving Beyond Moss for Plagiarism Detection General 8 min
Dr. Sarah Chen Dr. Sarah Chen 2 months ago

Why Some CS Departments Are Moving Beyond Moss for Plagiarism Detection

Riverdale State University’s computer science department spent years relying on Moss to catch plagiarised assignments. But as student work grew more sophisticated — combining copied web code, heavy refactoring, and AI-generated fragments — the department realised token-based similarity alone was no longer sufficient. This case study covers how they transitioned to a multi-tool detection pipeline.

Do AST-Based Engines Catch More Refactored Cheating Than Token-Based Ones General 10 min
Dr. Sarah Chen Dr. Sarah Chen 3 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.

The Open Source Audit That Nearly Bankrupted a Startup General 7 min
Dr. Sarah Chen Dr. Sarah Chen 4 months ago

The Open Source Audit That Nearly Bankrupted a Startup

When a promising fintech startup, Veritas Ledger, sought Series B funding, a standard due diligence audit spiraled into a crisis. Their core transaction engine, the product of a brilliant but rogue founding engineer, was built on stolen, copyleft-licensed code. The discovery didn't just delay the funding round; it put the company's very existence on the line. This is the story of how hidden code provenance almost destroyed a business.

The Open Source License Your Startup Can't Afford to Ignore General 8 min
Dr. Sarah Chen Dr. Sarah Chen 4 months ago

The Open Source License Your Startup Can't Afford to Ignore

You’ve vetted for GPL and MIT licenses, but AGPLv3 is a different beast. Its viral "network use" provision can force you to open-source your entire proprietary application. This is the license audit most engineering teams miss until they get the letter from a compliance firm.

Your Website's JavaScript Was Stolen Last Month General 8 min
Dr. Sarah Chen Dr. Sarah Chen 4 months ago

Your Website's JavaScript Was Stolen Last Month

A competitor's new feature looks suspiciously like yours. The JavaScript is minified, the variable names are changed, but the logic is identical. This is web code plagiarism, and it's rampant. Here’s how to prove it happened and what you can do about it, using a forensic approach that goes beyond simple string matching.

Your Static Analysis Tool Is Lying to You About Security General 5 min
Dr. Sarah Chen Dr. Sarah Chen 4 months ago

Your Static Analysis Tool Is Lying to You About Security

You’ve integrated a static analysis tool into your CI/CD pipeline. The security dashboard is green. But you’re still vulnerable. This is the dangerous gap between compliance checklists and actual security. We’ll show you what your SAST tool is missing and how to build a defense that works.

The 8 Code Smells That Predict Your Next Production Outage General 8 min
Dr. Sarah Chen Dr. Sarah Chen 5 months ago

The 8 Code Smells That Predict Your Next Production Outage

We analyzed post-mortems from 50 major production incidents. A pattern emerged: the same eight code smells were present in over 80% of the codebases. This isn't about style—it's about stability. Here’s what to look for and how to fix it before your system goes down.