JS Benchmarking (John Resig)

js-benchmark.js

// T-Distribution
var tDistribution = 2.776;
 
// Run the tests in order
runTest("Max Runs, Simple Test", test1, function(){

});
 
// Run the V8-style Max test (but with error determination)
function runTest(name, test, next){
  var runs = [], r = 0;
 
  setTimeout(function(){
    var start = (new Date).getTime(), diff = 0;
 
    for ( var n = 0; diff < 1000; n++ ) {
      test();
      diff = (new Date).getTime() - start;
    }
 
    runs.push( n );
 
    if ( r++ < 4 )
      setTimeout( arguments.callee, 0 );
    else {
      done(name, runs);
      if ( next )
        setTimeout( next, 0 );
    }
  }, 0);
}
 
// Run the SunSpider/Dromaeo style of test execution
function runTest2(name, test, num, next){
  var runs = [], r = 0;
 
  setTimeout(function(){
    var start = (new Date).getTime();
    test();
    runs.push( (new Date).getTime() - start );
 
    if ( ++r < num )
      setTimeout( arguments.callee, 0 );
    else {
      done(name, runs);
      if ( next )
        setTimeout( next, 0 );
    }
  }, 0);
}
 
// Calculate all the details from the resulting numbers
function compute(times, runs){
  var num = times.length, results = {runs: num};
 
  times = times.sort(function(a,b){
    return a - b;
  });
 
  // Make Sum
  results.sum = 0;
 
  for ( var i = 0; i < num; i++ )
    results.sum += times[i];
 
  // Make Min
  results.min = times[0];
      
  // Make Max
  results.max = times[ num - 1 ];
 
  // Make Mean
  results.mean = results.sum / num;
 
  var log = 0;
 
  for ( var i = 0; i < num; i++ ) {
    log += Math.log(times[i]);
  }
 
  results.geometric_mean = Math.pow(Math.E, log / num);
  
  // Make Median
  results.median = num % 2 == 0 ?
    (times[Math.floor(num/2)] + times[Math.ceil(num/2)]) / 2 :
    times[Math.round(num/2)];
  
  // Make Variance
  results.variance = 0;
 
  for ( var i = 0; i < num; i++ )
    results.variance += Math.pow(times[i] - results.mean, 2);
 
  results.variance /= num - 1;
      
  // Make Standard Deviation
  results.deviation = Math.sqrt( results.variance );
 
  // Compute Standard Errors Mean
  results.sem = (results.deviation / Math.sqrt(results.runs)) * tDistribution;
 
  // Error
  results.error = ((results.sem / results.mean) * 100) || 0;
 
  return results;
}
 
function test1(){
  $("#jq-siteLogo");
}
 
// Output the results
function done(name, runs){
  var results = compute(runs), str = "\n\n" + name + "\n----------------------------\n";
 
  for ( var i in results ) {
    str += i + ":\t\t" + results[i] + "\n";
  }
  console.log(str);
}