Practice Efficient Heap Construction - 36.4.2 | 36. Priority queues and heaps - Part B | Data Structures and Algorithms in Python
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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 do we place a new node in a heap?

πŸ’‘ Hint: This is done to maintain the complete tree structure.

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 time complexity does the delete max operation have in a max heap?

  • O(n)
  • O(log n)
  • O(1)

πŸ’‘ Hint: Think about the tree height.

Question 2

True or False: A leaf node in a heap always satisfies the heap property.

  • True
  • False

πŸ’‘ Hint: What do leaf nodes lack?

Solve 3 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

If you have an array of integers: [5, 3, 8, 4, 1, 7]. Construct a max heap using the bottom-up approach. Show the heap structure at each step.

πŸ’‘ Hint: Follow the process layer by layer while applying heap rules.

Question 2

Explain why heap sort is not stable and what implications that has. Provide an example to support your explanation.

πŸ’‘ Hint: Consider how data is removed and what order you extract elements.

Challenge and get performance evaluation