The average is probably not a good measure, you will also have to look at the spread around the average (i.e. the variance). Checking if the changes between your programs are significant (due to your changes in the program) or simply due to random (background) effects can be done by running an "ANOVA"-test. The NULL-hypothesis would then be that the variance between runs of the program before and after you changed it is not bigger than the variance within each run.

CountZero

A program should be light and agile, its subroutines connected like a string of pearls. The spirit and intent of the program should be retained throughout. There should be neither too little or too much, neither needless loops nor useless variables, neither lack of structure nor overwhelming rigidity." - The Tao of Programming, 4.1 - Geoffrey James

In reply to Re: What is the best way to compare profiling results before and after a code change? by CountZero
in thread What is the best way to compare profiling results before and after a code change? by ELISHEVA

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