Sarah leads AI-generated code research at Codequiry, focusing on how large-language-model output can be reliably distinguished from human-written code.
General
7 min
Dr. Sarah Chen
•
9 hours ago
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.
General
15 min
Dr. Sarah Chen
•
2 weeks ago
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.
General
12 min
Dr. Sarah Chen
•
2 weeks ago
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.
General
11 min
Dr. Sarah Chen
•
4 weeks ago
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.
General
8 min
Dr. Sarah Chen
•
1 month ago
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.
General
10 min
Dr. Sarah Chen
•
3 months ago
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.
General
7 min
Dr. Sarah Chen
•
3 months ago
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.
General
8 min
Dr. Sarah Chen
•
3 months ago
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.
General
8 min
Dr. Sarah Chen
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4 months ago
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.
General
5 min
Dr. Sarah Chen
•
4 months ago
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.
General
8 min
Dr. Sarah Chen
•
4 months ago
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.
General
9 min
Dr. Sarah Chen
•
4 months ago
Static analysis tools promise security but often deliver noise. They flag trivial formatting issues while missing the architectural vulnerabilities that lead to real breaches. Here are 10 glaring signs your security scanning is broken and what to do to fix it.