JavaScript Heap Coding Practice Problems

Heaps are an essential data structure in JavaScript used for efficiently managing priority-based tasks. A Heap is a specialized tree-based structure that allows for quick retrieval of the smallest or largest element, making it useful for priority queues, scheduling algorithms, and graph algorithms like Dijkstra’s shortest path.

This curated list of JavaScript Heap Coding Practice Problems will help you master heap operations. Whether you're a beginner or an experienced developer, these problems will enhance your understanding of heap construction, insertion, deletion, and heap-based algorithms, improving your problem-solving skills.

Heap Practice Problems

Easy

• Height of Heap
• Minimum Cost of Ropes
• Sum of Elements Between k1'th and k2'th Smallest Elements
• Huffman Decoding-1
• Gadgets of Doraland
• Kth Smallest
• Is Binary Tree Heap
• Kth Smallest Element in an Array
• Minimum Product of k Integers in an Array of Positive Integers
• Sort an Almost Sorted Array
• Top K Frequent Elements
• Height of a Complete Binary Tree (or Heap) with N Nodes
• Kth Smallest Element in a Row-wise and Column-wise Sorted 2D Array
• Sum of All Elements Between k1’th and k2’th Smallest Elements

Medium

• Heap Sort
• Check if a Binary Tree is a Min Heap
• Binary Heap
• How to Implement Priority Queue – Using Heap or Array?
• Find Kth Smallest Element in a Row-column Sorted Matrix
• Connect n Ropes with Minimum Cost
• Find K Closest Numbers
• Sort an Almost Sorted Array
• BST to Max Heap
• K’th Largest Element in a Stream
• Find the K Numbers with Most Occurrences in the Given Array
• Find the Kth Largest Element in an Array
• Merge Overlapping Intervals
• Game with String
• Nearly Sorted
• Rearrange Characters
• Minimum Sum of Squares of Character Counts
• K-th Largest Sum Contiguous Subarray

Hard

• Merge K Sorted Arrays
• Merge K Sorted Lists
• Find the Median of a Stream of Running Integers
• Smallest Range in K Lists
• Huffman Encoding
• Sliding Window Maximum (Maximum of All Subarrays of Size K)
• Merge Two Sorted Arrays in O(1) Extra Space Using Heap