Practice Naive Heap Construction - 36.4.1 | 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 for the insert operation in a max heap?

πŸ’‘ Hint: Think about how many levels can exist in the heap.

Question 2

Easy

Define what a max heap is.

πŸ’‘ Hint: Consider the relationships between parent and child nodes.

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 of the insert operation in a max heap?

  • O(1)
  • O(log n)
  • O(n)

πŸ’‘ Hint: Consider the maximum number of levels in the heap.

Question 2

True or False: A max heap allows for efficient access to the minimum element.

  • True
  • False

πŸ’‘ Hint: Think about what elements are prioritized in a max heap.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given an initial unsorted array of integers, devise a bottom-up heapify function and analyze its complexity.

πŸ’‘ Hint: Start your iteration from the index of the last non-leaf node.

Question 2

Write the code for the insert operation in a max heap, explaining how you ensure the max heap property is maintained after each insertion.

πŸ’‘ Hint: Think about how many comparisons you may need to ensure the node is in the right place.

Challenge and get performance evaluation