This repository contains implementations of various data structures in Golang. Each data structure is designed to provide efficient and flexible data storage and manipulation for different use cases.
The Hash Table is a data structure that stores key-value pairs and provides fast retrieval and insertion operations. It uses a hash function to map keys to their corresponding buckets, enabling constant-time average access.
The Heap is a specialized binary tree data structure that satisfies the heap property. It allows quick access to the maximum (or minimum) element and efficient insertion and deletion of elements. Heaps are often used in priority queues and sorting algorithms.
The Linked List is a linear data structure that consists of nodes linked together. Each node contains data and a reference to the next node, forming a chain-like structure. Linked lists allow efficient insertion and deletion operations, and they can be used to implement stacks, queues, and other data structures.
The Matrix is a two-dimensional data structure used to represent collections of elements in rows and columns. It provides efficient storage and manipulation of numerical data, making it useful for applications like linear algebra and image processing.
The Queue is a linear data structure that follows the First-In-First-Out (FIFO) principle. Elements are inserted at the end (rear) of the queue and removed from the front. Queues are commonly used in task scheduling, breadth-first search, and other scenarios where the order of processing matters.
The Stack is a linear data structure that follows the Last-In-First-Out (LIFO) principle. Elements are inserted and removed from the same end (top) of the stack. Stacks are useful for managing function calls, expression evaluation, and backtracking algorithms.
The Tree is a hierarchical data structure that consists of nodes connected by edges. Each node can have zero or more child nodes, and there is one special node called the root that has no parent. Trees are widely used for organizing hierarchical data and implementing search algorithms.
Contributions to this repository are welcome! If you have any improvements or new data structure implementations to add, feel free to create a pull request. Please ensure that your code is well-documented and passes the existing test cases.
Happy coding with data structures! 🚀