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CSE331 Lecture 8

# CSE331 Lecture 8 - Lecture 8 CSE 331 HW 1due today Q1 Q2...

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Lecture 8 CSE 331 Sep 15, 2011

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HW 1due today Q1, Q2 and Q3 in different piles I will not take any HW after 1:15pm
7 more to go… I’ll need confirmation in writing. No graded material will be handed back till I get this signed form from you!

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Solutions to HW 1 Handed out at the END of the lecture
HW 2 Has been posted (link on the blog by 3pm) Start early

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Definition-III Should scale with input size If N increases by a constant factor, so should the measure Polynomial running time At most c . N d steps (c>0, d>0 absolute constants) At most c . N d 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]

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The actual run times n! 100n 2 n 2 Asymptotic View Asymptotic View
Asymptotic Notation is O with glasses is Ω with glasses = is Θ with glasses

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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
g(n) is O(f(n)) g(n) n 0 c*f(n) for some c>0 n

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g(n) is Ω(f(n)) g(n) n 1 n ε*f(n) for some ε>0
Questions?

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