Empirical Measures
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Asymtotic measures are "analytical" meaning that we look at the algorithm and deduce it's behavior. Empirical measures are situational observations; we measure real behavior for a specific situation. They are complimentary to each other; empirical measures should validate our analytical view of program behavior. | Asymtotic measures are "analytical" meaning that we look at the algorithm and deduce it's behavior. Empirical measures are situational observations; we measure real behavior for a specific situation. They are complimentary to each other; empirical measures should validate our analytical view of program behavior. | ||
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| + | ==Empirical measurement of time== | ||
| + | Example using psuedocode to be written | ||
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| + | ==Empirical counting of operations== | ||
| + | Example using psuedocode to be written | ||
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Revision as of 15:55, 27 March 2009
Empirical analysis of a program is a factual enquiry carried out by simply recording what is observed or measured from actual run-time behavior of a program. Two of the more common empirical measures of program behavior are actual clock time and operations counting. Examples of operations counting: counting comparisons; counting assignments (memory writes); counting the number of times the inner most code in a loop is executed.
Asymtotic measures are "analytical" meaning that we look at the algorithm and deduce it's behavior. Empirical measures are situational observations; we measure real behavior for a specific situation. They are complimentary to each other; empirical measures should validate our analytical view of program behavior.
Empirical measurement of time
Example using psuedocode to be written
Empirical counting of operations
Example using psuedocode to be written
