submission.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;
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Plagiarism Detection
The MOSS replacement for professors and computer science departments. Check every submission against the class, GitHub, Stack Overflow, the web and AI, with line-by-line evidence for academic integrity reviews. 65+ languages.
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- Well Reviewed Code Plagiarism Checker Rated 4.72 out of 5
- Trusted By 500+ Universities Worldwide
- Since 2018 200K+ Users Worldwide
Used in programming courses at 500+ universities, including
23 students were flagged for academic honesty concerns this week.
Out of 33 checked. Another 40 matched a classmate's work. The latest three:
submission.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,
submission.cpp
87%
6 7Archive.AddData(, DifficultyInterval);8 9Archive.AddData(, ScorePerKill);10Archive.AddData(, ScorePerLevel);11Archive.AddData(, ScorePerLevelIncrease);12 13Archive.AddData(, PlayerRespawnTime);14Archive.AddData(, PlayerRespawnTimePerLevel);
Student names, comments and strings are removed before anything is shown here.
Teaching a programming course?
Run every assignment through the same review: against the open web, previous cohorts and the rest of the class.
Check your whole course Yearly plans for institutionsLine-by-line evidence
Every match, traced
to its source
Codequiry reads each submission line by line and shows exactly which lines match the open web, GitHub, AI-written code or another student in the course, each with its source and a similarity score.
cs-105 · lab_07 / wordle_solver.py
3 flagged sections
1# CS-105 Lab 7 jpatel42
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 = {}
28 return counts
29
30from typing import List, DictLines 30–41 · AI-written · 89%
31
32def best_next_guess(candidates: List[str]) -> str:
33 """Select the most informative next guess.
34 Args:
35 candidates: A list of remaining valid 5-letter words.
36 Returns:
37 The candidate that maximizes letter-frequency coverage.
38 """
39 freq: Dict[str, int] = letter_frequency(candidates)
40 score = lambda w: sum(freq.get(c, 0) for c in set(w))
41 return max(candidates, key=score)
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Yearly plans for institutions
Inside the report
Find plagiarism matches across every code source
Each submission is compared with the open web, public repositories and previous cohorts, and screened for AI-written code. The matched lines are set out side by side, ready for your review.
AI-written89%
Web & repo match92%
Run your first check in minutes. Yearly plans for institutions.
Check your course
How It Works
Check code for plagiarism
Check code for plagiarism
and similarity
Upload a set of submissions, choose the checks and review the evidence. Codequiry gives instructors a consistent, documented way to confirm that submitted work is a student's own.
01
Upload the submissions
Choose the programming language, drag in the submissions for an assignment and select the checks to run: peer comparison, the Codequiry database and the open web.
How the checks work
02
Follow the check as it runs
Progress is shown live while each check runs, and the report opens the moment it finishes. There is nothing to install and nothing to configure.
See a sample report
03
Review the evidence
Cluster graphs, match tables and score distributions show where to look first. Open any submission to see its matches highlighted and compared side by side.
Get started
What every check covers
Four checks,
Four checks,
one report
Peer comparison, web source matching and AI detection run together on every submission, on Hexagram and Zeus, the engines we build in-house. One report brings the findings together.
01
Peer Comparison
Compares every submission in the course with every other, using AST-level tokenization. Renamed variables and reordered functions are still matched.
02
Web Source Check
Matches code against GitHub, Stack Overflow, Chegg and billions of indexed sources, with a direct link to each one.
03
AI Code Detection
Screens each file for the patterns of code written by ChatGPT, Claude and Copilot, and reports how likely it is to be AI-written.
04
Evidence Summary
Brings the findings together, scores the risk for each submission and sets out the evidence. The determination stays with you.
Faculty decide. Codequiry supplies the evidence.
Built for faculty
Academic Dishonesty
Academic Dishonesty
Detection for Programming
Everything a department needs to uphold academic integrity in its programming courses. Purpose-built for computer science, not a text plagiarism checker adapted for code.
Side-by-Side Comparison
A line-by-line comparison with syntax highlighting, similarity scores and one-click navigation between matched sections.
Syntax highlighting
Click-to-navigate
Export to PDF
Visual Clustering
Interactive diagrams that show, at a glance, which submissions resemble one another.
AI Code Detection
Flags code likely written by ChatGPT or Copilot, file by file.
Whole-Cohort Checks
A course of 500 submissions is processed in under 10 minutes.
Source URL Tracking
A direct link to every place the code was found, for your records.
Public API
A REST API for custom integrations. Connect Codequiry to your grading pipeline and run checks automatically, at any scale.
REST API access
Webhooks
Full documentation
Codequiry, MOSS and Dolos
Why departments move
Why departments move
from MOSS to Codequiry
Feature
Codequiry
MOSS
Dolos
Peer comparison
Submissions compared with one another
Web source matching
GitHub, Stack Overflow and the open web
AI code detection
Code written by ChatGPT or Copilot
Structural analysis
Matches code after renaming and reordering
Visual report
Side-by-side evidence in the browser
65+ languages
Python, Java, C++, JavaScript and more
~24
~15
Hosted service
No installation required
Self-host
From the faculty
What professors say
What professors say
about Codequiry
In use at 500+ institutions worldwide
"Teaching over 500 students per term, we faced a critical challenge: detecting code copied from ChatGPT and online sources without viable tools. Codequiry enables us to batch-process entire cohorts efficiently. This technology is essential for maintaining rigorous standards in computer science education."
MIT
Senior Lecturer
"The rise of AI-generated code has made verifying student mastery a critical challenge. Codequiry is now essential for upholding our academic standards and ensuring every submission represents original effort."
Stanford University
Professor
"Codequiry actually works, detecting AI-generated code and web plagiarism that outdated tools miss. We finally have real enforcement backing our academic integrity policies."
Georgia Tech
Lecturer
"We found a 99% match between a student and a Chegg solution. I can't believe CS departments are missing this."
University of Toronto
Professor
"Used MOSS for years but it couldn't catch web plagiarism at all. Students figured that out fast."
Carnegie Mellon
Professor
"Love that I can exclude my starter code. Used to get tons of false matches because everyone had the same template."
University of Michigan
Lecturer
"Been using it 2 years now. Solid. Does what it says."
Arizona State
Instructor
65+ languages
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Source code plagiarism detection for programming courses, in use at 500+ institutions worldwide. Start with a single course or license the whole department.
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