Practice Array Representation of Heaps - 36.3 | 36. Priority queues and heaps - Part B | Data Structures and Algorithms in Python
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

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

πŸ’‘ Hint: Think about the height of the tree.

Question 2

Easy

Where is the maximum element in a max heap located?

πŸ’‘ Hint: Recall that the root is where we start accessing the heap.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the time complexity for the insert operation in a heap?

  • O(n)
  • O(log n)
  • O(1)

πŸ’‘ Hint: Remember the height of the tree.

Question 2

Is the maximum element always at the root of a max heap?

  • True
  • False

πŸ’‘ Hint: Consider the properties of heaps.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given the array representation of a max heap, [25, 18, 14, 8, 7, 6, 3], remove the max element and show the resulting heap.

πŸ’‘ Hint: Consider the restoration process of heap property.

Question 2

If a max heap is built from the following numbers: 10, 15, 30, 5, 20, what will be the max heap array after full construction?

πŸ’‘ Hint: Insert them one-by-one to visualize the heap building process.

Challenge and get performance evaluation