Practice Building A Heap (36.4) - Priority queues and heaps - Part B - Data Structures and Algorithms in Python
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Building a Heap

Practice - Building a Heap

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the time complexity of inserting a node into a heap?

💡 Hint: Consider the height of the heap.

Question 2 Easy

Where is the maximum value located in a max heap?

💡 Hint: Think about the heap property.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What operation does the root of a max heap represent?

Minimum Value
Maximum Value
Average Value

💡 Hint: Think about what makes a max heap.

Question 2

True or False: The time complexity of building a heap using the naive method is linear.

True
False

💡 Hint: What happens when you keep adding elements one by one?

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given an array of integers, perform a series of insertions to build a max heap step by step. Describe your actions.

💡 Hint: What happens with every insert?

Challenge 2 Hard

Analyze the efficiency of constructing a heap versus using other data structures like balanced binary trees for priority queues.

💡 Hint: Why might you choose heaps for priority queues?

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.