Practice Building a Heap - 36.4 | 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: Consider the height of the heap.

Question 2

Easy

Where is the maximum value located in a max heap?

πŸ’‘ Hint: Think about the heap property.

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 operation does the root of a max heap represent?

  • Minimum Value
  • Maximum Value
  • Average Value

πŸ’‘ 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

πŸ’‘ Hint: What happens when you keep adding elements one by one?

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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

πŸ’‘ Hint: What happens with every insert?

Question 2

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

πŸ’‘ Hint: Why might you choose heaps for priority queues?

Challenge and get performance evaluation