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    <p>There are many ways to measure performance, and the "right" way to do it depends a lot on what you are actually doing. Quite often, the simple way to determine performance is simply to let the application do what it normally does, and just measure the time - if it takes long enough, just using a stop-watch (e.g. an app for the mobile phone, function on actual wrist-watch or similar) will work just great. For shorter periods of time, you may need other methods - going all the way down to using "CPU clock cycles" with the "TSC" - timestamp counter in the CPU itself. </p> <p>If it's something that only takes a short amount of time, but your application will do a lot of it, then running the same code many times. </p> <p>For other applications, because the time spent isn't really spent using CPU clock cycles, it gets harder - for example, if part of your application is reading some large file, then the CPU time used may only be 2-3%, the rest of the time is spent waiting for the hard-disk to fetch the data from the actual disks in there. </p> <p>If the application is using networking, again, the CPU probably only uses a few percent of the time that it takes to send a packet of data over a 1GB network link. </p> <p>The type of data, and the way the data is organized, sorted, and used will also matter. If you insert something to be sorted from a source that is already sorted, it may perform completely differently from a list of items that are unsorted - and surprisingly, it can be better OR worse, depending on how the data is being stored/sorted. </p> <p>It can be quite hard to "look at code" and determine its performance. There are so many other factors than "what the code looks like" that affects it. </p> <p>If you have an existing application that works, measuring it's performance, and using profiling software to see how much time is spent where is a good plan. </p>
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    1. USMats Petersson
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