6 kinds of analysis worst case usually average case

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Kinds of analysis Worst-case (usually) Average-case (sometimes) Best-case
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Worst-case: (usually) The worst-case efficiency of an algorithm is its efficiency for the worst-case input of size n, which is an input (or inputs) of size n for which the algorithm runs the longest among all possible inputs of that size. • T(n) = maximum time of algorithm on any input of size n.
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Average-case: (sometimes) T(n) = expected time of algorithm over all inputs of size n. • Need assumption of statistical distribution of inputs.
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Best-case: The best-case efficiency of an algorithm is its efficiency for the best-case input of size n, which is an input (or inputs) of size n for which the algorithm runs the fastest among all possible inputs of that size
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How to devise(develop) algorithms Something of an art form Cannot be fully automated We will describe some general techniques and try to illustrate when each is appropriate
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Expressing Algorithms Implementations Pseudo-code English My main concern here is not the specific language used but the clarity of your expression
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Verifying algorithm correctness Proving an algorithm generates correct output for all inputs One technique covered in textbook Loop invariants: A loop invariant is a condition that is necessarily true immediately before and immediately after each iteration of a loop .
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Analyzing algorithms The “process” of determining how much resources (time, space) are used by a given algorithm We want to be able to make quantitative assessments about the value (goodness) of one algorithm compared to another We want to do this WITHOUT implementing and running an executable version of an algorithm
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