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Questions and Answers
What does efficiency analysis focus on?
What does efficiency analysis focus on?
- Algorithm operation count growth (correct)
- Mathematical asymptotic notations
- Time complexity
- Input value (n
What is the purpose of efficiency analysis?
What is the purpose of efficiency analysis?
- To determine the color of an algorithm
- To focus on the order of growth of an algorithm's operation count (correct)
- To analyze the taste of an algorithm
- To analyze the smell of an algorithm
What happens to the running time value as n value increases?
What happens to the running time value as n value increases?
- It stays the same
- It fluctuates
- It decreases
- It increases (correct)
What does time complexity express?
What does time complexity express?
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Which notation represents the upper bound value, expressing worst-case complexity?
Which notation represents the upper bound value, expressing worst-case complexity?
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What does O(g(n)) represent?
What does O(g(n)) represent?
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Study Notes
- Efficiency analysis focuses on algorithm operation count growth.
- Running time value increases with n value.
- Input value (n) is proportional to algorithm complexity.
- Time complexity is expressed as T(n) = Cop * C(n).
- Mathematical asymptotic notations describe algorithm time complexity.
- Asymptotic complexity measure is the foundation of this method.
- Big OH (O) represents the upper bound value, expressing worst-case complexity.
- Big OMEGA (Ω) represents the lower bound value, expressing best-case complexity.
- Big THETA (Θ) represents the average bound value, expressing average-case complexity.
- O(g(n)) is the set of functions that grow no faster than g(n).
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