Practice Complexity Of Insert (36.1.1) - Priority queues and heaps - Part B
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Complexity of Insert

Practice - Complexity of Insert

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the time complexity for inserting an element into a max heap?

💡 Hint: Think about the height of the tree and how a balanced tree behaves.

Question 2 Easy

Explain why the maximum value in a max heap is always at the root.

💡 Hint: Consider what would happen if this property didn't hold.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the time complexity for inserting a node in a binary max heap?

O(n)
O(log n)
O(1)

💡 Hint: Consider how many levels you traverse.

Question 2

True or False: In a max heap, the root node is always the smallest element.

True
False

💡 Hint: Recall the definition of a max heap.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Construct a max heap from the array [10, 15, 30, 5, 20, 25, 35] using the bottom-up heapify method. Illustrate each step.

💡 Hint: Focus on how each parent compares to its children and adjust accordingly.

Challenge 2 Hard

Explain how using an array representation for heaps improves access and manipulation of nodes compared to a traditional tree structure.

💡 Hint: Consider the arithmetic relationship between indices for parent and children.

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