Practice Memoization Technique - 24.2.4 | 24. Module – 02 | Design & Analysis of Algorithms - Vol 2
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is memoization?

💡 Hint: Think about how it relates to reducing repetitive work.

Question 2

Easy

What is the base case in recursion?

💡 Hint: It's the stopping point for recursion.

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 term refers to storing previously computed results in a recursive function?

  • Recursion
  • Memoization
  • Dynamic Programming

💡 Hint: Think about the technique that helps speed up function calls.

Question 2

True or False: Memoization can improve the time complexity of certain recursive algorithms.

  • True
  • False

💡 Hint: Consider the effect on redundant calculations.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Implement a function using memoization to calculate the nth Fibonacci number in Python.

💡 Hint: Think about how to store each result in a dictionary or a similar structure.

Question 2

Given the overlapping subproblems property, compare memoization performance with simple recursion in terms of function calls for Fibonacci(6). Show how many calls are made without and with memoization.

💡 Hint: Calculate recursive calls manually or trace them out in a tree diagram.

Challenge and get performance evaluation