Held: Wednesday, 19 February 2003
Summary: Today we consider techniques for comparatively evaluating the running time of algorithms.
speed. That is, we consider how long the algorithm takes to run.
asymptoticin that we look at the behavior as the input gets larger.
Big-Oof an algorithm.
for big enough n.
sizeof the input (e.g., the number of items in a list or vector to be manipulated).
elementof the input. Finding the smallest element in a list is often an O(n) algorithm.
divide and conquer.
unimportantbecause they can be
hiddenin the d.
countthe steps in an algorithm and then add them up. After you've taken combinatorics, you can use recurrence relations.
Thursday, 15 January 2003 [Samuel A. Rebelsky]
Wednesday, 19 February 2003 [Samuel A. Rebelsky]
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