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This repository contains a collection of C++ programs related to graph theory and data structures. Each program is designed to demonstrate various algorithms and techniques commonly used in computer science.

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💎 C++ Data Structures & Graph Theory

Welcome to the data-structures-practical repository! This collection houses various C++ programs showcasing fundamental concepts in graph theory and data structures. From implementations of graph representations to algorithms like Depth-First Search (DFS), Breadth-First Search (BFS), and Prim's algorithm, this repository offers hands-on learning opportunities for both students and developers interested in algorithms and C++ programming.

Feel free to explore the programs, study their implementations, and use them as a reference for your own projects. Contributions and feedback are always appreciated!

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

C++ Compiler:

You need a C++ compiler installed on your system. Common choices include: GCC (GNU Compiler Collection): Available on Unix-based systems like Linux and macOS. You can install it using package managers like apt (for Ubuntu/Debian) or Homebrew (for macOS).

Clang:

Another popular compiler, often used as an alternative to GCC. It's also available on Unix-based systems. Microsoft Visual C++ Compiler: If you're on Windows, you might use Visual Studio's compiler or the standalone Microsoft Visual C++ Compiler, which comes with Visual Studio Build Tools or Visual Studio Community edition.

Text Editor or Integrated Development Environment (IDE):

You'll need a text editor to write your C++ code. Many developers prefer using specialized IDEs like Visual Studio, Visual Studio Code, CLion, Xcode, or Eclipse. However, you can also use lightweight text editors like Sublime Text, Atom, or Vim.

Knowledge of C++ Syntax:

Understanding the basics of C++ syntax, data types, control structures, functions, and classes is essential for writing and running C++ programs.

Installation

A step by step guide that will tell you how to get the development environment up and running. Follow these steps to compile and run the C++ programs in this repository:

Install a C++ Compiler: Ensure you have a C++ compiler installed on your system. Common choices include:

GCC (GNU Compiler Collection):

Available on Unix-based systems like Linux and macOS.

Clang:

Another popular compiler, often used as an alternative to GCC.

Microsoft Visual C++ Compiler:

If you're on Windows, you might use Visual Studio's compiler or the standalone Microsoft Visual C++ Compiler.

Don't forget to ⭐ the repository first!

Then fork the repository.

Clone the Repository:

Clone this repository to your local machine using the following command:

git clone https://github.com/your-username/your-repository.git

Replace your-username and your-repository with your GitHub username and the name of your repository.

Navigate to the Repository:

Change your current directory to the cloned repository:

 cd your-repository

Compile the Programs:

Compile the C++ programs using your preferred compiler. For example, using GCC:

g++ -o AdjacencyList AdjacencyList.cpp
g++ -o AdjacencyMatrix AdjacencyMatrix.cpp
g++ -o DFSBFS DFSBFS.cpp
g++ -o Hashing Hashing.cpp
g++ -o Prims Prims.cpp

Run the Programs:

Execute the compiled programs by running their respective binaries. For example:

    ./a.exe

Explore and Experiment: Feel free to explore the programs, study their implementations, and experiment with different inputs and scenarios.

Contribute and Share: If you find any issues or have suggestions for improvements, don't hesitate to open an issue or submit a pull request. Sharing your insights can help improve the quality of this repository for everyone!

Happy coding!

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This repository contains a collection of C++ programs related to graph theory and data structures. Each program is designed to demonstrate various algorithms and techniques commonly used in computer science.

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