analyzing algorithms

• measure the quality or efficiency of an algorithm so that we may compare algorithms that perform similiar tasks
• want this messure to be machine independent
• we will need to consider the number of intructions that need to be executed
• function of the input size, n
• vary depending on "chance"
• HOW WE EVALUTE ALGORITHMS THAT DO THE SAME THING: their time complexities
  • T of a (n) = 10n → O(n)
  • T of b (n) = n^2 → O(n)^2
    • n < 10 → B is better
    • n > 10 → A is better
• what we really care about is the order of growth

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