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* The Original Code is JavaScript Engine testing utilities.
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* Igor Bukanov
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var gTestfile = 'regress-313967-01.js';
//-----------------------------------------------------------------------------
var BUGNUMBER = 313967;
var summary = 'Compile time of N functions should be O(N)';
var actual = '';
var expect = '';
printBugNumber(BUGNUMBER);
printStatus (summary);
function F(x, y) {
var a = x+y;
var b = x-y;
var c = a+b;
return ( 2*c-1 );
}
function test(N)
{
var src = F.toSource(-1)+"\n";
src = Array(N + 1).join(src);
var counter = 0;
src = src.replace(/F/g, function() { ++counter; return "F"+counter; })
var now = Date.now;
var t = now();
eval(src);
return now() - t;
}
var times = [];
for (var i = 0; i != 10; ++i) {
var time = test(1000 + i * 2000);
times.push(time);
gc();
}
var r = calculate_least_square_r(times);
print('test times: ' + times);
print("r coefficient for the estimation that eval is O(N) where N is number\n"+
"of functions in the script: "+r);
print( r < 0.97 ? "Eval time growth is not linear" : "The growth seems to be linear");
reportCompare(true, r >= 0.97, summary);
function calculate_least_square_r(array)
{
var sum_x = 0;
var sum_y = 0;
var sum_x_squared = 0;
var sum_y_squared = 0;
var sum_xy = 0;
var n = array.length;
for (var i = 0; i != n; ++i) {
var x = i;
var y = array[i];
sum_x += x;
sum_y += y;
sum_x_squared += x*x;
sum_y_squared += y*y;
sum_xy += x*y;
}
var x_average = sum_x / n;
var y_average = sum_y / n;
var sxx = sum_x_squared - n * x_average * x_average;
var syy = sum_y_squared - n * y_average * y_average;
var sxy = sum_xy - n * x_average * y_average;
var r = sxy*sxy/(sxx*syy);
return r;
}