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Growth of Functions

Growth of Functions. CS 46101 Section 600 CS 56101 Section 002 Dr. Angela Guercio Spring 2010. Asymptotic Notation. O-notation O(g(n )) = { f(n ) : there exist positive constants c and n 0 such that 0 ? f(n ) ? c g(n ) for all n ? n 0 }. Asymptotic Notation.

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383 views • 19 slides

Growth of Functions

Growth of Functions. CIS 606 Spring 2010. Asymptotic Notation. O-notation O(g(n )) = { f(n ) : there exist positive constants c and n 0 such that 0 ? f(n ) ? c g(n ) for all n ? n 0 }. Asymptotic Notation. g(n ) is an asymptotic upper bound for f(n )

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457 views • 18 slides

Running Time

Running Time. Experimental Studies. Write a program implementing the algorithm Run the program with inputs of varying size and composition Use a method like System.currentTimeMillis() to get an accurate measure of the actual running time Plot the results. Limitations of Experiments.

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273 views • 15 slides

Algorithm/Running Time Analysis

Algorithm/Running Time Analysis. Running Time. Why do we need to analyze the running time of a program? Option 1: Run the program and time it Why is this option bad? What can we do about it?. Pseudo-Code. Used to specify algorithms Part English, part code Algorithm (arrayMax(A, n))

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236 views • 13 slides

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Constant n0 - PowerPoint PPT Presentation

Growth of Functions

Growth of Functions

Running Time

Algorithm/Running Time Analysis