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Heap in C++ STL - make_heap(), push_heap(), pop_heap(), sort_heap(), is_heap, is_heap_until()

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 2K+ Views

A heap is a complete binary tree data structure where parent nodes are either greater than (max heap) or less than (min heap) their children. C++ STL provides several heap operations through the header that work with containers like vectors. Basic Heap Operations make_heap() and front() The make_heap() function converts a range in a container to a heap structure. Use front() to access the largest element in a max heap ? #include using namespace std; int main() { vector heap = {33, 43, 53, 38, 28}; make_heap(heap.begin(), heap.end()); cout

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Check if a number is an Achilles number or not in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 350 Views

An Achilles number is a number that is powerful but not a perfect power. A powerful number means that for every prime factor p, p² also divides the number. A perfect power is a number that can be expressed as a^b where a and b are positive integers and b > 1. Some examples of Achilles numbers are: 72, 108, 200, 288, 392, 432, 500, 648, 675, 800, 864, 968, 972, 1125. Understanding Achilles Numbers For example, 108 is an Achilles number because: 108 = 2² × 3³ (powerful: both 2² and 3² divide 108) ...

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Check if a number is a Trojan Numbers in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 211 Views

A Trojan Number is a special type of number that meets two criteria: it must be a strong number but not a perfect power. A strong number is one where every prime factor appears at least twice (squared or higher). For example, 72 = 2³ × 3² is strong because both prime factors (2 and 3) appear at least twice, and it's not a perfect power like 8 = 2³. Understanding Strong Numbers A number is strong when every prime factor appears with an exponent of 2 or more ? from math import sqrt def ...

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Check if a king can move a valid move or not when N nights are there in a modified chessboard in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 466 Views

Suppose we have an infinite chessboard with the same rules as chess. Given N knights and a king's position, we need to check whether the king is in checkmate or not. The coordinate system is bounded by large values like (-10^9

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Check if a key is present in every segment of size k in an array in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 225 Views

Suppose we have an array A with N elements, we have another value p and a segment size k, we have to check whether key p is present in every segment of size k in A. So, if the input is like A = [4, 6, 3, 5, 10, 4, 2, 8, 4, 12, 13, 4], p = 4 and k = 3, then the output will be True because: Segment 1: [4, 6, 3] contains 4 ✓ Segment 2: [5, 10, 4] contains 4 ✓ Segment 3: [2, 8, 4] contains 4 ✓ Remaining elements: [12, ...

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Check if a given Binary Tree is Heap in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 681 Views

A binary heap is a special binary tree with two key properties: it must be a complete tree (all levels filled except possibly the last, which fills left to right), and it must satisfy the heap property (each parent node is greater than or equal to its children for a max-heap). In this article, we'll implement a solution to check if a given binary tree satisfies both heap properties. Understanding Heap Properties A binary tree is a valid max-heap if: Complete Tree Property: All levels are completely filled except possibly the ...

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Check if a given Binary Tree is height balanced like a Red-Black Tree in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 214 Views

A Red-Black Tree is a balanced binary search tree where the height difference is controlled. In such trees, the longest path from any node to a leaf is at most twice the length of the shortest path. This property ensures the tree remains balanced and provides efficient operations. We need to check if a given binary tree satisfies this height-balanced property where for every node, the longest leaf-to-node path is not more than double the shortest path from node to leaf. Problem Understanding Given a binary tree like this: ...

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Check for balanced parentheses in an expression O(1) space O(N^2) time complexity in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 545 Views

Checking for balanced parentheses is a classic programming problem. While the typical stack-based approach uses O(n) space, this article presents an O(1) space solution with O(n²) time complexity that modifies the string in-place by marking processed characters. Algorithm Overview The algorithm uses three global variables to track state and processes closing brackets by finding their matching opening brackets ? cnt ? counts unmatched opening brackets i ? current position in the string j ? position of the last unmatched opening bracket How It Works When a closing bracket is found, the solve() ...

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Find the Largest Cube formed by Deleting minimum Digits from a number in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 222 Views

Suppose we have a number N, we have to determine the largest perfect cube that can be generated by removing minimum digits (possibly 0) from the number. We can delete any digit from the given number to reach the target. As we know a number N is called a perfect cube if N = M³ for some integer M. So, if the input is like 806, then the output will be 8, as we can delete 0 and 6 from the number, then we will get 8, which is perfect cube of 2. Algorithm To solve this, ...

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Find the largest Complete Subtree in a given Binary Tree in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 357 Views

A complete binary tree is one where all levels are completely filled except possibly the last level, and the last level has all keys as far left as possible. In this problem, we need to find the largest complete subtree within a given binary tree and return its size. So, if the input is like ? 50 30 60 5 ...

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