1. Lecture 9
CSE 331
Sep 20, 2010

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HW clarifications
HW grading rubric
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5. 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”

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

7. The actual run times n!
100n2
Asymptotic View n2

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

9. 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

10. Questions?

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