🧩 Problem Solving Algorithms & Data Structures Repository

🎯 Master Coding Interviews & Competitive Programming | 📚 Learn Data Structures & Algorithms | 🚀 System Design Patterns

A comprehensive open-source collection of problem-solving algorithms, data structures, and system design implementations in TypeScript/JavaScript. Perfect for coding interview preparation, competitive programming, and computer science education. This monorepo contains 500+ solutions for various coding challenges including HackerRank problems, LeetCode-style questions, algorithmic implementations, and scalable system design patterns.

🔍 Keywords: algorithms data-structures coding-interview hackerrank leetcode typescript javascript competitive-programming system-design interview-preparation computer-science software-engineering dynamic-programming graph-algorithms technical-interview

📁 Project Structure

.
├── codespaces/
│   ├── hackerrank/           # HackerRank challenge solutions
│   │   ├── DynamicProgram/   # Dynamic programming problems
│   │   ├── Strings/          # String manipulation problems
│   │   ├── MultiPointers/    # Two-pointer technique problems
│   │   ├── Search/           # Search algorithm problems
│   │   ├── Sortings/         # Sorting algorithm problems
│   │   ├── Implementation/   # Implementation challenges
│   │   └── Constructive Algo/ # Constructive algorithms
│   ├── MergeInterval/        # Merge interval algorithm implementations
│   └── system-design/       # System design patterns and solutions
├── package.json              # Root package.json with workspace configs
├── tsconfig.base.json        # Base TypeScript configuration
└── eslint.base.js           # Base ESLint configuration

🚀 Workspaces

• @problem-solving/hackerrank: Comprehensive solutions to HackerRank challenges organized by category
• @problem-solving/algorithms: Implementation of classic algorithms and merge interval problems
• @problem-solving/system-design: System design problems, patterns, and architectural solutions

🛠️ Tech Stack

• TypeScript/JavaScript - Primary programming languages
• Node.js - Runtime environment
• Yarn Workspaces - Monorepo management
• ESLint - Code linting and quality assurance
• Prettier - Code formatting
• ts-node - TypeScript execution environment

🏁 Getting Started

Prerequisites

• Node.js (version 18+)
• Yarn package manager

Installation

# Clone the repository
git clone <repository-url>
cd problems-solving

# Install dependencies for all workspaces
yarn install

Development Commands

# Build all workspaces
yarn build

# Start development mode (runs React workspace)
yarn dev

# Lint all workspaces
yarn lint

# Fix linting issues across all workspaces
yarn lint:fix

# Format code in all workspaces
yarn format

# Type check all workspaces
yarn type-check

# Clean build artifacts
yarn clean

📝 Workspace-specific Commands

You can run commands for individual workspaces:

# HackerRank solutions
yarn workspace @problem-solving/hackerrank dev
yarn workspace @problem-solving/hackerrank build
yarn workspace @problem-solving/hackerrank lint

# Algorithm implementations
yarn workspace @problem-solving/algorithms dev
yarn workspace @problem-solving/algorithms build

# System design
yarn workspace @problem-solving/system-design dev
yarn workspace @problem-solving/system-design build

📚 Problem Categories

HackerRank Solutions

• Dynamic Programming: Optimal substructure and overlapping subproblems
• String Algorithms: Pattern matching, anagrams, and string manipulation
• Two Pointers: Efficient array/string traversal techniques
• Search Algorithms: Binary search, linear search variations
• Sorting Algorithms: Custom sorting implementations and applications
• Implementation: Logic and simulation problems
• Constructive Algorithms: Building solutions step by step

Core Algorithms

• Merge Intervals: Overlapping interval problems and solutions
• Data Structures: Implementation of fundamental data structures
• Graph Algorithms: Traversal, shortest path, and connectivity problems

System Design

• Scalability Patterns: Load balancing, caching, database sharding
• Architecture Patterns: Microservices, event-driven architecture
• Distributed Systems: Consensus algorithms, fault tolerance

🧪 Running Solutions

Most solutions can be executed directly:

# Run a specific TypeScript solution
cd codespaces/hackerrank/DynamicProgram/CommonChild
ts-node index.ts

# Run JavaScript solutions
node solution.js

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/new-algorithm)
3. Commit your changes (git commit -am 'Add new algorithm implementation')
4. Push to the branch (git push origin feature/new-algorithm)
5. Create a Pull Request

Code Style

• Follow TypeScript/JavaScript best practices
• Use meaningful variable and function names
• Add comments for complex algorithms
• Include time and space complexity analysis
• Ensure all linting rules pass

📄 License

This project is open source and available under the MIT License.

📧 Contact

For questions or suggestions, please open an issue or reach out via email.

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