This problem, also referred to as the “sliding window maximum” problem, can be efficiently solved using heaps. We’ve already discussed an O(n) solution.

Both methods provide effective solutions for finding the kth smallest element in a list of numbers. Understanding their strengths and trade-offs will help you select the most suitable approach for your use case.

Chef has opened up a new restaurant. He picks out the positive reviews and posts it on the website of the restaurant. A review is considered to be positive if it is among the top one-third of the total reviews when they are sorted by their rating.

The Heap data structure is an array that can be viewed as a complete Binary Tree. Each node in the tree corresponds to an element of the array A[].
In this post we will learn about, how to build min/max Heaps using STL.

In the last post we discussed about C++ Standard Template Library (STL) Linked List. In this post we will learn about STL Priority queue and using it as Max/Min Heap. A priority queue is a data structure for maintaining a set of elements having an associated value.

Huffman codes are a widely used technique for compressing data. Huffman codes is a greedy algorithm to build up an optimal way of representing each character as a binary string. Suppose we have a 10,000 character data file that we wish to store. And we observe a character ‘a’ occurs very frequently.