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Code plagiarism detection,
built for academic integrity.

Check every submission against the class, GitHub, Stack Overflow, the web and AI-written code. Results in minutes, in 65+ languages.

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Monthly plans for one course or a whole department. Cancel anytime.

Used in programming courses at 500+ universities since 2018
  • Harvard University
  • Stanford University
  • MIT
  • UC Berkeley
  • Carnegie Mellon University
  • University of Illinois Urbana-Champaign
  • Georgia Tech
A Codequiry report: LibrarySystem.java is 98% similar to code found online, with internet matches from GitHub Gist and Stack Overflow listed by score Side-by-side comparison: a pasted C++ snippet against a GitHub repository, 78% copied, same code and names with only spacing and one message changed
65+programming languages
427B+code sources
200K+reports run
5,000+CS courses since 2018

What instructors say

Faculty and course teams have trusted Codequiry with their programming courses since 2018.

4.72 from 5,152 verified reviews
As a professor at Stanford, I want to make sure students submit code they wrote themselves. Codequiry checks source code for plagiarism on the web, which other checkers can't do.
Professor, Stanford University
Codequiry protects our course from copying. It's the only tool we found reliable.
Course instructor
The best experience I've had checking source code for plagiarism on the web. They even cover Stack Overflow!
Codequiry user

82 submissions matched code found online this week.

Out of 3,924 checked. Another 364 matched a classmate's work. The latest three:

Pythonsubmission.py 95%
22def __init__( 23 self, 24 num_states=100,25 num_actions=4, 26 alpha=0.2, 27 gamma=0.9, 28 rar=0.5, 29 radr=0.99, 30 dyna=0,
44 lines copied word for word Found on the web 11 hours ago
Csubmission.h 77%
10struct FQPProjectileParams11{12 FFloatPoint Location;13 FFloatPoint Direction;14 float Damage = 0.f;15 float Speed = 0.f;16 17 std::shared_ptr<FTexture> Texture = nullptr;18 std::string TargetTag;
12 lines copied Found on the web 11 hours ago
C++submission.cpp 87%
6 7Archive.AddData(, DifficultyInterval);8 9Archive.AddData(, ScorePerKill);10Archive.AddData(, ScorePerLevel);11Archive.AddData(, ScorePerLevelIncrease);12 13Archive.AddData(, PlayerRespawnTime);14Archive.AddData(, PlayerRespawnTimePerLevel);
8 lines copied Found on the web 13 hours ago

Student names, comments and strings are removed before anything is shown here.

See exactly which lines were copied.

Every line of a submission is checked. Each flagged block tells you where it came from: a web page, GitHub, an AI model or a classmate.

cs-105 · lab_07 / wordle_solver.py 3 flagged sections
1# CS-105 Lab 7
2import random # for picking starter words later
3 
4WORDS = open("words.txt").read().split()
5# print(len(WORDS)) # debug, should be ~12k
6 
7def score_guess(guess, answer):Lines 7-17 · Chegg · 97%
8 feedback = ["miss"] * 5
9 answer_chars = list(answer)
10 for i in range(5):
11 if guess[i] == answer[i]:
12 feedback[i] = "hit"
13 answer_chars[i] = None
14 for i in range(5):
15 if feedback[i] == "miss" and guess[i] in answer_chars:
16 feedback[i] = "close"
17 answer_chars.remove(guess[i])
18 return feedback
19 
20# TODO: cache this between rounds??
21def filter_words(words, guess, feedback):Lines 21-25 · GitHub · 94%
22 return [w for w in words if score_guess(guess, w) == feedback]
23 
24def letter_frequency(words):
25 counts = {}
26 return counts
27 
28from typing import List, DictLines 28-37 · AI-written · 89%
29 
30def best_next_guess(candidates: List[str]) -> str:
31 """Select the most informative next guess.
32 Args:
33 candidates: A list of remaining valid 5-letter words.
34 """
35 freq: Dict[str, int] = letter_frequency(candidates)
36 score = lambda w: sum(freq.get(c, 0) for c in set(w))
37 return max(candidates, key=score)

This is an example. Your own reports link to the real source of every flagged block.

Upload a folder. Get evidence you can stand behind.

  • One check covers it all: classmates, past terms, GitHub, Stack Overflow, the web and AI.
  • Renames don't hide anything: reordered functions and new variable names still match.
  • Works where you grade: Canvas, the API, the command line and an MCP server.
Get started See example checks
The new assignment panel: drop ZIP files, choose what to compare against, then upload and scan

What you see when a check finishes.

The overview, the matched lines side by side, the AI score and every place a match was found. These are screens from the product, not mockups.

dashboard.codequiry.com/results/overview
Codequiry plagiarism detection dashboard showing student submission analysis Side-by-side code comparison with highlighted plagiarism matches AI detection analysis showing a code block flagged as AI-written with probability score and signals Submissions dashboard listing student files with peer, web, and AI plagiarism scores per submission Detection tools configuration with web, GitHub, Stack Overflow, Gist, Software Heritage, and AI detection sources

65+ languages.
Nothing to set up.

Upload the files the way students hand them in. Codequiry works out the language and compares the structure of the code, not just the text, from Python to COBOL.

  • Python
  • JavaScript
  • Java
  • C++
  • C#
  • PHP
  • C
  • TypeScript
  • Swift
  • Kotlin
  • Rust
  • Go
  • Ruby
  • SQL
  • R
  • MATLAB
  • Haskell
  • Scala
  • Dart
  • Elixir
  • Assembly
  • Objective-C
  • Julia
  • Groovy
  • Haxe
  • HTML5
  • Lua
  • Markdown
  • Pascal
  • Perl
  • +35 more

Used MOSS before?
Here's what changes.

MOSS compares the files you upload with each other. Codequiry does that too, then checks the web, GitHub and AI-written code, and shows it all in one report you read in the browser.

MOSS

Stanford's free script, since 1994
  • Only compares the files you upload to each other
  • Can't tell you if code was written by AI
  • About 24 languages
  • Submit from a script, read results on a plain web page
  • Rate-limited, academic use only, no support

Codequiry

What a check covers here
  • Classmates and past terms, plus the web, GitHub and Stack Overflow
  • AI-written code flagged (ChatGPT, Claude, Copilot)
  • 65+ programming languages
  • Matched lines side by side, in your browser
  • Our own engines, Hexagram and Zeus
HexagramCodequiry’s own code-similarity engine, built in-house. It took inspiration from winnowing, then grew into our own tokenization system, with stronger false-positive reduction, more languages and multi-language checks, web-source matching, bulk processing and better base-code detection. v2.0.1Our main engine. It compares the structure of the code, so renamed variables and reordered functions still match.
Zeus Detection SuiteBuilt on Hexagram and tuned for speed, with AI-written code detection alongside it.

Questions instructors ask us

How the code plagiarism checker works, which languages it reads, what the AI code detector catches and how it compares to MOSS.

More answers in the help center →
What is the best code plagiarism checker for programming assignments?

Codequiry is a code plagiarism checker built for source code, not essays. It compares every submission with the rest of the class and with web sources like GitHub and Stack Overflow, reads the structure of the code in 65+ programming languages, and puts it all in one report with the matched lines side by side.

Does Codequiry work as a programming plagiarism checker for any language?

Yes. As a programming plagiarism checker it covers 65+ programming languages, including Python, Java, C++, JavaScript, C#, Go and Rust, with nothing to set up. Renamed variables, reordered functions and rewritten comments still match. Submissions are compared with each other and with 427B+ public code sources.

Is Codequiry an AI code detector as well as a plagiarism checker?

Yes. The same report runs an AI code detector that flags code written by ChatGPT, GitHub Copilot, Claude and Gemini, in 65+ languages. You see copied code and AI-written code in one place, which MOSS and text checkers don't do.

Is Codequiry a good alternative to MOSS?

Yes. Codequiry does what MOSS does, comparing submissions with each other, then adds web and GitHub matching, AI-written code detection and 65+ programming languages. It runs on our own engines, Hexagram and Zeus. That is why people use it as a MOSS alternative.

What engines does Codequiry use to detect source code plagiarism?

Two of our own. Hexagram is the original engine we built in-house. It started from the idea behind winnowing and grew into its own tokenization system. Zeus builds on Hexagram and is tuned for speed.

Can MOSS detect AI-written code from ChatGPT or Copilot?

No. MOSS only measures how similar the uploaded files are to each other, and it has no AI detection. Codequiry includes an AI code detector that flags code generated by ChatGPT, Claude and GitHub Copilot.

Is Codequiry affiliated with Stanford MOSS?

No. Hexagram is Codequiry's own engine. It took inspiration from winnowing, then grew into our own tokenization system with fewer false positives, more languages, web matching, bulk processing and better base-code detection. Zeus builds on Hexagram for speed, and MOSS Winnow is our large-batch engine on the same tokenization.

How many programming languages does Codequiry support compared to MOSS?

Codequiry supports 65+ programming languages, including Python, Java, C++, JavaScript, Go and Rust, with nothing to configure. MOSS supports about 24.

How is Hexagram better than MOSS for code plagiarism detection?

Hexagram is our in-house MOSS alternative, built for comparing the structure of code, so renames and reordering still match. Zeus builds on Hexagram for faster analysis. Our published comparison shows results on specific examples. Scores always depend on the assignment and how much the code was changed.

Just one assignment to check?

Run a Deep Scan and get the same report, with no account or subscription.

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Monthly plans for one course or a whole department. Cancel anytime.

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