Data Structures and Algorithms in Go

This page contains a list of commonly used Data Structures and Algorithms in Golang. The source code examples of all the Golang Data Structures and Algorithms are up-to-date and are well-tested in our development environment.

Data structures and algorithms are very important for programmers to learn and apply in real-time project design and development.

Data Structures in Go (Golang)

A data structure is a specialized format for organizing, processing, retrieving, and storing data. It provides a means to manage vast amounts of data efficiently, and large-scale datasets would be nearly unmanageable without robust data structures.

• Golang Stack Data Structure Implementation
• Queue Implementation in Golang 
• Priority Queue Implementation in Golang 
• Golang Linked List Implementation
• Binary Tree Implementation in Golang 
• Golang Doubly Linked List Implementation
• Circular Linked List Implementation in Golang 
• Binary Search Tree Implementation in Golang
• Golang AVL Tree Implementation
• Hash Table Implementation in Golang
• Golang Set Data Structure Implementation
• Golang Two-Dimensional Array

Algorithms in Go (Golang)

An algorithm is a step-by-step procedure or formula for solving a problem. It's a sequence of steps to perform to achieve a particular output. Algorithms can be represented as pseudocode or flowcharts, among other formats.

• Bubble Sort Algorithm in Golang 
• Heap Sort Algorithm in Golang
• Golang Interpolation Search Algorithm
• Golang Recursion Algorithm
• Golang Binary Search Algorithm
• Golang Linear Search Algorithm
• Golang Quick Sort Algorithm
• Golang Merge Sort Algorithm
• Golang Shell Sort Algorithm
• Golang Insertion Sort Algorithm
• Golang Selection Sort Algorithm
• Golang Binary Search Tree with Example

Understanding the right data structure and algorithm to use for a given scenario can greatly improve the efficiency (in terms of runtime and memory usage) of software applications. This knowledge becomes especially vital when dealing with large datasets or when performance is a critical aspect of the application.