Lecture 9 CSE 331 Sep 20, 2010

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Hope you’re following the blog HW clarifications HW grading rubric Nice summaries of the lectures

http://xkcd.com/124/

At most c.Nd steps (c>0, d>0 absolute constants) Definition-III Should scale with input size If N increases by a constant factor, so should the measure Polynomial running time At most c.Nd steps (c>0, d>0 absolute constants) Step: “primitive computational step”

Reading Assignments Sections 1.2, 2.1, 2.2 and 2.4 in [KT]

The actual run times n! 100n2 Asymptotic View n2

Asymptotic Notation ≤ is O with glasses ≥ is Ω with glasses

Run time of an algorithm (Worst-case) run time T(n) for input size n Maximum number of steps taken by the algorithm for any input of size n

Questions?

Today’s agenda Definition of asymptotic notations Properties of asymptotic notations Asymptotic running time Analyzing the running time of the GS algo