AlgoMaster - Engineering Algorithm Simulator

A comprehensive educational platform for engineering students to master algorithms and computer science concepts through interactive visualizations and simulations.

✨ Features

🏠 Modern Homepage

• Responsive Design: Beautiful gradient-based UI with modern animations
• Interactive Navigation: Easy access to all subjects and tools
• Student-Focused: Built specifically for engineering students' needs
• Professional Layout: Header, main content sections, and informative footer

📚 Covered Subjects

Automata Theory

• Finite Automata (DFA): Interactive state transition simulator
• Context-Free Grammar: Parser and derivation tree generator
• Regular Expressions: Pattern matching and regex testing
• Turing Machines: Step-by-step execution simulator

Design & Analysis of Algorithms (DAA)

• Greedy Algorithms: Fractional Knapsack, Job Sequencing, Prim's MST, Kruskal's MST
• Dynamic Programming: 0/1 Knapsack with DP table visualization
• Divide & Conquer: Merge Sort with step-by-step visualization
• Backtracking: N-Queens with interactive chessboard

Operating Systems

• Disk Scheduling: FCFS, SSTF, SCAN, C-SCAN algorithms
• Page Replacement: FIFO, LRU, Optimal algorithms
• Page Replacement: LRU, FIFO, and other page replacement algorithms

🛠️ Tech Stack

• Framework: Next.js 15 with TypeScript
• Styling: Tailwind CSS
• Charts: Custom SVG-based visualizations
• State Management: React Hooks

📁 Project Structure

src/
├── app/
│   ├── daa/                    # Design & Analysis of Algorithms
│   │   ├── greedy/            # Greedy algorithms
│   │   ├── dynamic/           # Dynamic programming
│   │   ├── divide-conquer/    # Divide and conquer
│   │   └── backtracking/      # Backtracking algorithms
│   ├── auto/                   # Automata Theory
│   │   ├── finite-automata/   # FA simulations
│   │   ├── regular-expressions/ # Regex tools
│   │   ├── context-free-grammar/ # CFG parsers
│   │   └── turing-machines/   # TM simulators
│   ├── os/                     # Operating Systems
│   ├── components/             # Reusable React components
│   └── utils/                  # Algorithm implementations

🚀 Getting Started

Prerequisites

• Node.js 18 or later
• npm or yarn

Installation

1. Clone the repository:

git clone <repository-url>
cd algo-simulator

2. Install dependencies:

npm install

3. Run the development server:

npm run dev

4. Open http://localhost:3000 in your browser.

👥 Contributing

This is a collaborative group project. To contribute:

1. Create a new branch for your feature:

git checkout -b feature/algorithm-name

2. Make your changes and commit:

git add .
git commit -m "Add: Algorithm name implementation"

3. Push to your branch:

git push origin feature/algorithm-name

4. Create a Pull Request on GitHub

Contribution Guidelines

• Follow consistent naming conventions
• Add proper TypeScript types
• Include step-by-step algorithm visualization
• Update this README if adding new features
• Test your implementations before submitting

📋 TODO / Roadmap

Algorithms to Implement

• String Matching Algorithms (KMP, Rabin-Karp)
• Branch & Bound Algorithms (TSP, 0/1 Knapsack)
• Graph Algorithms (Dijkstra, Floyd-Warshall)
• Sorting Algorithms (Quick Sort, Heap Sort)

Automata Theory Enhancements

• NFA to DFA Conversion
• Pushdown Automata Simulator
• Multi-tape Turing Machines
• Regular Expression to FA Conversion

Features

• Save/Load automata configurations
• Export visualizations as images
• Step-by-step animation controls
• Mobile-responsive design

🤝 Team Members

• Yash Jadhav - Project Lead & Core Development (LinkedIn)
• Vaishnavi Sawant - Algorithm Implementation & UI/UX Design (LinkedIn)

📧 Contact

For questions, suggestions, or collaboration:

• Email: help.algomaster@gmail.com
• Project: AlgoMaster - Engineering Algorithm Simulator

📝 License

This project is created for educational purposes.

🎯 Learning Objectives

Students using this simulator will be able to:

• Understand algorithm complexity and visualization
• Trace through algorithm execution step-by-step
• Visualize data structures and state transitions
• Compare different algorithmic approaches
• Gain hands-on experience with theoretical concepts

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Note: This is an educational project designed to help students understand complex algorithms and automata theory through interactive visualization.