So far we've looked at implementation of tree data structure and some of it's variants such as trie. In this post, we'll dive into heaps. These are also referred to as priority queues.
Introduction
Heap is a variant of tree data structure, with two a...

George

Future

Community Picks is a section on daily.dev where our community members share the most interesting and valuable content they've discovered online. From insightful articles to handy tools, every post is a gem curated by our dedicated coomunity. To contribute to Community Picks, you need to have at least 250 reputation points, ensuring that only active and trusted members can share their finds.

Community Picks

Heaps, also known as priority queues, are a type of tree data structure where every node satisfies the heap property, either as a max-heap or min-heap. Heaps are complete binary trees and can be efficiently represented using arrays. Key operations include adding and removing elements while maintaining the heap property. The time complexity for these operations is O(log(n)), while heapify has an asymptotic complexity of O(n). Converting a min-heap to a max-heap can be done by inserting negated keys.

Heaps in JavaScript

Permalink Creating a heap using an exisiting array

<p>Great explanation of heaps in Java! The breakdown of min-heap and max-heap operations like insertion and deletion is really clear. It might also be helpful to include a few real-world use cases, like how heaps are used in priority queues or algorithms like Dijkstra’s. Overall, solid post!</p>
