Module
Asymptotic Analysis and Complexity Measures
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About
Big-O/Θ/Ω notation, worst-case running time, common growth rates, basic models of computation, and relating input size to time/space. Grounds every later analysis. Draws on discrete math (sums, logs, induction).
Goal
Given pseudocode, derive tight asymptotic bounds (including simple recurrences by unfolding or substitution); compare algorithms rigorously using O/Θ/Ω; and explain why constants and lower-order terms are suppressed.
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