computer-science

This story was originally published on HackerNoon at: https://hackernoon.com/mastering-maps-in-go-everything-you-need-to-know.
Learn about using maps in Go (golang), including associative arrays, hash maps, collision handling, and sync.Map, with practical code examples.
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This story was written by: @smokfyz. Learn more about this writer by checking @smokfyz's about page, and for more stories, please visit hackernoon.com.

This article covers the essentials of using maps in Go programming, from basic associative arrays to advanced hash maps with collision handling strategies. It delves into the implementation of maps in Go, how to manage concurrency with sync.Map, and provides practical examples to illustrate map operations and their complexities. The discussion aims to equip you with the knowledge to effectively use maps in various programming scenarios, enhancing both efficiency and performance.

This story was originally published on HackerNoon at: https://hackernoon.com/java-algorithms-coding-a-binary-tree-right-side-view-leetcode.
In this article, you will learn how to code a Binary Tree Right side view in LeetCode.
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This story was written by: @rakhmedovrs. Learn more about this writer by checking @rakhmedovrs's about page, and for more stories, please visit hackernoon.com.

Given the root of a binary tree, imagine yourself standing on the right side of it. Then, return the values of the nodes you can see ordered from top to bottom. I would say it’s a pretty popular question during coding interviews Using simple words — think of the level for a particular node in a binary tree as the depth of that node. This code gives us linear time and space complexity, and it performs pretty well.

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-merge-two-sorted-lists.
We can use LinkedList to merge both sorted lists, though there are considerations to doing it single or double-linked that may complicate the operation.
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The list should be made by splicing together the nodes of the first two lists. It could be singly linked or doubly linked. The number of nodes in both lists is in the range `[0, 50]`-100 <= 100` The first Linked node is usually called the head whereas the last one is called the tail. The solution has a solution and we’ll discuss it in terms of big O notation. We’re looking for a node with minimal value stored in it. We move the pointer to the next for LinkedList which has a head. We also need a current node for storing the link of the current node.

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-implement-trie-prefix-tree-blind-75-leetcode-questions.
A trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings.
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This story was written by: @rakhmedovrs. Learn more about this writer by checking @rakhmedovrs's about page, and for more stories, please visit hackernoon.com.

Trie is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker. The Trie data structure is the classic data structure that is widely used in text searching. We need to implement Trie with the following method: Trie() and Trie.insert(). In the real example of Trie we had to introduce a small part of the data structure which consists of smaller pieces called **Tree. nodes.

This story was originally published on HackerNoon at: https://hackernoon.com/implementing-a-singly-or-doubly-linked-list-in-java-a-leetcode-question.
Design your implementation of the linked list. You can choose to use a singly or doubly linked list.
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This story was written by: @rakhmedovrs. Learn more about this writer by checking @rakhmedovrs's about page, and for more stories, please visit hackernoon.com.

This task may help you to build or improve your skill of dividing tasks into smaller pieces. It can be solved in many different ways that if we are to describe them you’ll be bored and tired of reading that amount of information. I’m pretty sure many of you struggle to understand how this data structure works and where it works can be used to help you understand how it works. I suggest diving deeper and implementing our version of LinkedList, where you can be able to understand where this data works.