Trackera

Trackera is a premium, full-featured Student Coding Practice and Progress Tracking Platform designed to help students master Data Structures & Algorithms (DSA), build coding streaks, and prepare for placement interviews. The platform combines comprehensive dashboard visualizations, Monaco Editor-powered coding workspaces, and an AI-backed Coding Assistant.

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Key Features

• 📊 Dynamic Dashboards: Full analytics detailing coding statistics, placement offers, problem-solving progress, and streaks.
• 🔥 GitHub-style Coding Heatmap: A contribution calendar tracking student's daily coding activities.
• 💻 Problem Workspace: A premium environment featuring the Monaco Editor, multiple programming language supports, dynamic output compiling, and testcase verification.
• 🤖 AI Assistant: A generative AI-powered tutor that offers code reviews, algorithmic hints, and debugging suggestions in real-time.
• 🏢 Placement & Target Tracking: Set target companies, track placement preparations, and manage active job applications.
• 🛡️ Role-Based Security: Complete Student and Administrator dashboards with fully secure, JWT-based authentication.
• 📄 AI Resume Analyzer: Generates ATS compatibility score, detailed resume feedback, key strengths and weaknesses, missing industry-relevant skills, and actionable improvement recommendations.

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Technology Stack

Backend

• Node.js & Express.js (REST API)
• MongoDB with Mongoose (Database & ODM)
• JSON Web Tokens (JWT) (Secure authentication)
• Cors & Dotenv (Middleware and configurations)

Frontend

• React.js (Vite-powered SPA)
• Tailwind CSS (Premium glassmorphic styling)
• Monaco Editor React (Coding editor)
• Recharts (Progress charts)
• Lucide Icons (UI Icons)
• Axios (API Client)

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⚙️ Project Structure

Trackera/
├── backend/
│   ├── controllers/      # Route logic handlers (Auth, Practice, AI, etc.)
│   ├── middleware/       # JWT Authorization middleware
│   ├── models/           # Mongoose schemas (User, Problem, Submission, etc.)
│   ├── routes/           # REST API Route endpoints
│   ├── scripts/          # Seeding scripts for problems
│   ├── utils/            # Calculation utilities (Stats aggregations)
│   └── server.js         # Entrypoint configuration
│
└── frontend/
    ├── src/
    │   ├── components/   # Logo, StatCard, Heatmap, Charts, Dashboards
    │   ├── pages/        # Auth, Student Dashboard, Problem Workspace, AI Assistant
    │   ├── services/     # API Axios client integrations (Auth, Practice, AI)
    │   ├── App.jsx       # Routing configurations
    │   └── main.jsx      # DOM mounting point

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Installation & Local Setup

1. Prerequisites

Ensure you have Node.js and MongoDB installed and running on your system.

2. Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Install dependencies:

   npm install

3. Configure the Environment: Create a .env file from the example:

   cp .env.example .env

   Provide your PORT, MONGODB_URI, JWT_SECRET, and optional GEMINI_API_KEY for the AI assistant.
4. Seed the Problem Database:

   node scripts/seedProblems.js

5. Start the backend:

   npm start

3. Frontend Setup

1. Navigate to the frontend directory:

   cd ../frontend

2. Install dependencies:

   npm install

3. Start the Vite dev server:

   npm run dev

4. Access the web interface at http://localhost:5173.

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🤖 AI Resume Analyzer Configuration & Usage

The AI Resume Analyzer evaluates resume PDFs against industry standards and software engineering job description parameters using the Google Gemini API.

Setup Steps

1. API Key Setup: Obtain a Gemini API key from the Google AI Studio.
2. Environment Variable Configuration: Open backend/.env (and backend/.env.example) and add the key:

   GEMINI_API_KEY=your_google_gemini_api_key

   Note: If the key is omitted or left as dummy-key, the system automatically falls back to an intelligent mock parser for offline development/testing.

Usage Instructions

1. Navigate to AI Tools -> Resume Analyzer in the Student Dashboard.
2. Drag and drop your resume PDF or click to browse and select a file.
3. The upload progress will be shown.
4. View your ATS Score Gauge, Executive Summary, Strengths, Weaknesses, Missing Skills, and Recommendations on the premium results screen.
5. Revisit previous analyses by clicking on them in the Analysis History sidebar, or delete old ones using the trash icon.

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📄 License

This project is licensed under the MIT License.