Practice Course Schedule (1.6) - Design and Analysis of Algorithms - Design & Analysis of Algorithms

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8 questions

Flashcard drill
3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
2 questions · about 1 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define asymptotic complexity.
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Think about how algorithms perform on larger datasets.
Question 2.
What is Big O notation used for?
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Consider how we measure algorithm efficiency.
3Question 3.
What does Big O notation primarily measure?
- Memory consumption
- Time complexity
- Algorithm correctness
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Think about how we gauge efficiency in algorithms.
4Question 4.
True or False: Greedy algorithms always result in the optimal solution.
- True
- False
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Consider edge cases where greedy choices might lead to suboptimal results.
Question 5.
Propose a situation where a greedy algorithm might yield a suboptimal solution and discuss why that happens.
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Look into examples of change-making problems.
Question 6.
Design a small algorithm that uses dynamic programming to optimize a problem. Provide the steps involved.
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Think about how overlapping sub-problems can be stored.

4 more questions in this section. Enroll free to practise them all.