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4 cards from this section. Quick, good the night before a test.
Explain what Big O notation represents.
Think about the maximum time taken as input size grows.
When would you use Omega notation?
Consider the minimum performance of an algorithm.
Which notation is used to describe the upper bound of an algorithm's time complexity?
Think about maximum performance analysis.
True or False: Theta notation signifies that two functions grow at the same rate.
Consider both sides of the function bounded.
For a function defined as f(n) = 5n^3 + 10n^2 + 3, determine if it is Θ(n^3) and explain why.
Look for asymptotic behavior and the significance of leading terms.
Show that n log n is not O(n^(1.5)). Provide a detailed argument and some calculations.
Consider limits and behaviors of both functions as `n` increases.
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