Aim

To develop a responsive, full-stack, peer-driven web platform that enables competitive programming integrity management by providing users with secure reporting mechanisms and equipping high-rated moderators with clinical tools to review, catalog, and search cheating incidents transparently.

Introduction

CF Community Watch is a modern web application designed to simplify and democratize integrity moderation within global competitive coding networks. It allows users to flag contest infractions easily by providing specific contest/problem IDs along with cloud-hosted screenshot evidence, while automatically delegating review privileges to verified senior community members (Rating 1500+). With built-in features including a public paginated cheater database, real-time search functionality, an automated testing suite, and secure identity-matched authentication, CF Community Watch offers a comprehensive, secure, and clinical solution for tracking and evaluating contest violations efficiently.

Technologies

Frontend: React 19, Vite 8, TypeScript, React Router v7, Tailwind CSS v4, Premium Vanilla CSS

Backend: Node.js (ES Modules), Express.js

Database: MongoDB Atlas with Mongoose ODM

Authentication: JSON Web Tokens (JWT), BcryptJS, and Two-Step Codeforces Identity Verification

Image Uploads: Multer & Cloudinary SDK

Testing Suite: Jest, Supertest, and Shell Scripting (test-api.sh)

Security & Validation: Express Validator, Helmet headers

Version Control: Git & GitHub

Methodology

Requirement Analysis: Identified the critical need for an objective, evidence-centric platform where community members can report infractions transparently, mitigating the risks of anonymous hearsay and delayed platform-wide official sweeps.

System Design: Designed a modular full-stack architecture cleanly separating the React client view, Express server router, and MongoDB data layers. Configured strict database schemas for users, reports, independent reviews, and cryptographic verification challenges.

Frontend Development: Built using React 19, Vite 8, and TypeScript for robust type safety. Structured layout elements with Tailwind CSS v4 while applying high-end, premium Vanilla CSS for custom design tokens, glassmorphism UI overlays, micro-interactions, and theme parameter controllers.

Backend Development: Developed an Express.js engine utilizing modern ES Modules. Created a modular API framework containing segregated routes for authentication challenges, report filing pipelines, multipart image processing, and public database query distribution.

Two-Step Codeforces Authentication Flow: To prevent identity spoofing, an interactive validation pipeline was implemented:

Initiate Challenge: The user inputs their profile handle. The server queries the Codeforces API to confirm the handle exists, creates a unique CW-VRFY-[RANDOM_SUFFIX] token, and stores it as a temporary database challenge. The user then pastes this token into their official Codeforces Organization settings profile field.

Validation: The user triggers verification on the platform. The server executes a live API call to inspect the user's public Codeforces settings. If the organization token matches, registration is completed, user rating metrics determine role privileges (User vs Moderator), and a stateless JWT session is established.

Cloud & File Upload Integration: Integrated Multer middleware to process incoming multipart form-data, safely handling evidence snapshots by routing them to Cloudinary for optimized cloud hosting and CDN delivery.

Testing Suite Implementation: Configured an automated checking layer using Jest and Supertest to evaluate routing logic, role-restricted endpoint accessibility, validation strings, and database interactions alongside custom manual diagnostics run via a dedicated shell environment script.

Results

Developed a fully responsive, peer-driven ecosystem that allows community members to file structured misconduct reports with live image evidence.

Automated the authorization framework by linking user roles directly to live metrics fetched via external Codeforces API checks.

Provided high-rated moderators with an isolated, secure board interface to review active listings, append auditing comments, and modify verification status metrics.

Generated a clinical, publicly indexed database tracking confirmed infractions, supporting instant real-time lookups across handles and individual contest IDs.

Achieved continuous integration testing stability by maintaining integrated Jest and Supertest regression architectures.

Conclusion

The CF Community Watch platform successfully introduces a decentralized, clinical framework for regulating integrity inside competitive programming spaces. By integrating interactive cryptographic profile checks, automated rating restrictions, secure cloud storage pipelines, and consensus-driven moderation thresholds, the application provides an elegant, scalable toolset that empowers programmers to actively protect fair play in online matches.

Future Scope

Implementing automated code plagiarism engines utilizing AST (Abstract Syntax Tree) comparison tools directly within backend worker threads.

Setting up automated Webhook integrations to push immediate infraction updates to external community channels like Discord or Telegram.

Developing a dedicated counter-claim and appeal management module allowing flagged users to submit technical defenses against moderator rulings.

Expanding the analytical layout with predictive tracking engines to chart cheating trends across regions, timezones, and institutions.

Launching a specialized mobile app bundle using React Native to offer on-the-go moderation alerts and database lookups.

References

Codeforces Official API Developer Documentation

React 19 & Vite 8 Core Technical Guides

MongoDB Atlas Optimization and Mongoose Schemas Design Docs

Cloudinary SDK Integration Architecture Frameworks

Jest & Supertest API Route Validation Guides

Mentors and Mentees Details

Mentors:

Shashank S

Sucheth K Katte

Prabhav P

Mentees:

Shourya Sharma

Asaph Samuel

Shivanshu Muppana

Meda Sarayu

Kanike Charan Kumar

Tamidala Suharshini


Github Repository: https://github.com/assaampuhel/community-watch

Google meet link: meet.google.com/ihn-jhpc-uwb