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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define input size in relation to algorithms.
💡 Hint: Think about how we quantify the data in an algorithm.
Question 2
Easy
What does worst-case analysis help us understand?
💡 Hint: Consider scenarios where inputs might be challenging.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does 'input size' refer to in algorithm analysis?
💡 Hint: Focus on what metrics influence algorithm performance.
Question 2
True or False: The average case analysis is always more informative than the worst-case analysis.
💡 Hint: Think about when you would want maximum performance assurance.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
In an algorithm that sorts an array, what is the worst-case scenario when determining the time complexity? Illustrate this with an example.
💡 Hint: Think of sorting methods and how they operate on data.
Question 2
Discuss how changing the representation of graphs (adjacency matrix vs. adjacency list) affects the complexity of operations and the definition of input sizes.
💡 Hint: Visualize how graph data structures differ and their relationship with operations.
Challenge and get performance evaluation