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3 cards from this section. Quick, good the night before a test.
What is the Big O notation for the function t(n) = 50n?
Focus on the highest-order term.
Is t(n) = 200 + 3n² O(n²)?
Analyze the dominant term in the function.
What does Big O notation describe?
Think about the limits of efficiency
True or False: O(n²) means the algorithm runs slower than O(n).
Reflect on growth rates of these functions.
Consider three functions: f(n) = 2n², g(n) = 100n, and h(n) = 10. What is the asymptotic behavior of the total f(n) + g(n) + h(n)?
Identify the leading term that dominates the growth as n increases.
Prove that sorting an array of n elements requires at least Ω(n log n) comparisons in the worst case.
Think about how comparisons contribute to sorting efficiency.
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