This repository contains a collection of common data structures implemented in [programming language]. Each data structure is accompanied by comprehensive unit tests to ensure functionality and correctness.
Understanding and implementing data structures is fundamental to computer science. This repository serves as a resource for [programming language] developers to explore and learn about various data structures commonly used in software development.
A Binary Tree is a hierarchical data structure composed of nodes where each node has at most two children, referred to as the left child and the right child. The topmost node in a binary tree is called the root. Binary trees are widely used in computer science for tasks such as searching, sorting, and hierarchical representation of data.
A Simple Linked List is a linear data structure in which elements are stored in nodes, and each node points to the next node in the sequence. It consists of nodes, where each node contains data and a reference (or link) to the next node in the sequence. Linked lists provide dynamic memory allocation, efficient insertion and deletion operations, but they do not allow random access to elements like arrays.
A Double Linked List is a variation of a linked list in which each node has two links, one pointing to the next node in the sequence (like in a simple linked list), and another pointing to the previous node. This bidirectional linkage enables traversal in both forward and backward directions. Double linked lists offer advantages such as easier node removal and insertion operations compared to simple linked lists.
To get started with this repository, follow these steps:
-
Clone the repository to your local machine and navigate to the folder:
git clone https://github.com/G4lile00/data-structures.git && cd data-structures
-
Install the necessary dependencies:
npm -
npm install
Contributions are welcome! If you'd like to contribute to this repository fell free to do so.
This project is licensed under the [Apache 2.0] - see the LICENSE.md file for details.