Measuring impact on interactive tasks

[scott thomason <scott@thomasons.org>]

It crossed my mind while load testing some scheduler tunable settings 
that completely subjective monitoring of X jerkiness perhaps wasn't 
the most scientific way of measuring the interactive impact of the 
tunables. I'm no Evil Scientist, but I whipped up a perl script that 
I think accomplishes something close to capturing those statistics. 
It captures 1000 samples of what should be a precise .2 second delay 
(on an idle system it is, with a tiny bit of noise). 

Here's the script, along with some output produced while the system 
was under considerable load (around 13). Would something like this be 
worth developing further to help rigorously measure the interactive 
impact of the tunables? Or is there a flaw in the approach? (Jokes 
about Perl are considered below the belt...)
---scott


#!/usr/bin/perl

use strict;
use warnings;

use Time::HiRes qw/sleep time/;

my %pause = ();

for (my $x = 0; $x < 1000; $x++) {
  my $start = time();
  sleep(.2);
  my $stop = time();
  my $elapsed = $stop - $start;

  $pause{sprintf('%01.3f', $elapsed)}++;
}

foreach (sort(keys(%pause))) {
  print "$_:  $pause{$_}\n";
}

exit 0;


Sample output

time ./int_resp_timer.pl 
0.192:  1
0.199:  1
0.200:  10
0.201:  201
0.202:  53
0.203:  25
0.204:  22
0.205:  21
0.206:  34
0.207:  29
0.208:  29
0.209:  100
0.210:  250
0.211:  120
0.212:  35
0.213:  16
0.214:  17
0.215:  14
0.216:  9
0.217:  1
0.218:  3
0.219:  3
0.220:  1
0.222:  1
0.233:  1
0.303:  1
0.304:  1
0.385:  1

real    3m28.568s
user    0m0.329s
sys     0m1.260s