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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define asymptotic complexity.
💡 Hint: Think about how we measure algorithm performance as input scales.
Question 2
Easy
What does a greedy algorithm do?
💡 Hint: Recall the approach involves local optimal choices.
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 Big O notation used for?
- To measure algorithm correctness
- To measure algorithm efficiency
- To structure code
💡 Hint: It's about evaluating how algorithms behave with larger inputs.
Question 2
True or False: A greedy algorithm guarantees the best solution.
- True
- False
💡 Hint: Think about local versus global optimality.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Devise a way to compare the efficiency of two sorting algorithms using Big O analysis. What factors would you consider?
💡 Hint: Focus on how input sizes influence performance differences.
Question 2
Design an original algorithm to solve a real-life problem using either greedy approach or dynamic programming. Justify your method.
💡 Hint: Choose problems with overlapping subproblems for dynamic programming.
Challenge and get performance evaluation