There are a lot of microbenchmark tips out pn the internet. The intent of them differs from author to author.Today I want to show how you could compare e.g. different algorithms. You could simply do:

int COUNT = 1000000;
long firstMillis = System.currentTimeMillis();
for(int i = 0; i < COUNT; i++) {
  runAlgorithm();
}
System.out.println("Mean runtime of algorithm in seconds:"+(System.currentTimeMillis()-firstMillis) / 1000.0 / COUNT);

There are several problems with this approach, which results in very unpredictable results:

1. Make sure the variable COUNT is high enough (if runAlgorithm() is unexpensive). Then make sure you run this code several times. Additionally you should measure the RMS either for each runAlgorithm call or at the end of this code snippet for a better comparison with other algorithms.
2. You should turn off the JIT-compiler with specifying -Xint as a JVM option, otherwise your outcome could depend on the (unpredictable) JIT and not on your algorithm.
3. You should start with enough memory, so specify e.g.-Xms64m -Xmx64m. Because JVM memory allocation could get time consuming.
4. Quit all other applications or at least you should use

   long firstNanos = mx.getCurrentThreadCpuTime();
   ThreadMXBean mx = ManagementFactory.getThreadMXBean();

   instead of

   long firstMillis = System.currentTimeMillis();

5. Avoid that the garbage collector runs while your measurement: -Xnoclassg
   But make sure you have enough memory!

After this I got relative stable results: The difference of maximal and minimal value for the result is less then 4% after 10 runs.

From http://karussell.wordpress.com