A Heap is a specialized tree-based data structure that satisfies the heap property: If A is a parent node of B, then the key (the value) of node A is ordered with respect to the key of node B with the same ordering applying across the heap. A heap can be classified further as either a “max heap” or a “min heap”. In a max heap, the keys of parent nodes are always greater than or equal to those of the children and the highest key is in the root node. In a min heap, the keys of parent nodes are less than or equal to those of the children and the lowest key is in the root node.

The heap is one maximally efficient implementation of an abstract data type called a priority queue, and in fact priority queues are often referred to as “heaps”, regardless of how they may be implemented. A common implementation of a heap is the binary heap, in which the tree is a complete binary tree. The heap data structure, specifically the binary heap, was introduced as a data structure for the heapsort sorting algorithm. Heaps are also crucial in several efficient graph algorithms such as Dijkstra’s algorithm. In a heap, the highest (or lowest) priority element is always stored at the root. A heap is not a sorted structure and can be regarded as partially ordered. There is no particular relationship among nodes on any given level, even among the siblings. When a heap is a complete binary tree, it has a smallest possible height—a heap with N nodes always has log N height. A heap is a useful data structure when you need to remove the object with the highest (or lowest) priority.

Below is the list of commonly asked interview questions that uses heap data structure-

- Introduction to Priority Queues using Binary Heaps

- Min Heap and Max Heap Implementation in C++

- Min Heap and Max Heap Implementation in Java

- Heap Sort (Out-of-place and In-place implementation in C++ and C)

- Check if given array represents min heap or not

- Convert Max Heap to Min Heap in linear time

- Find K’th largest element in an array

- Sort a K-Sorted Array

- Merge M sorted lists of variable length

- Find K’th smallest element in an array

- Find smallest range with at-least one element from each of the given lists

- Merge M sorted lists each containing N elements

- External merge sort

- Huffman Coding

- Find first k maximum occurring words in given set of strings

- Find first k non-repeating characters in a string in single traversal

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