Exception for Kahan's Unum-Targeted Monster

• could not determine a ground truth

  1. y = 12.309990923302163

Specification

\[1 \leq y \land y \leq 9999\]

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{y \cdot y + 1}\\ t_1 := \left|y - t_0\right| - \frac{1}{y + t_0}\\ t_2 := t_1 \cdot t_1 + {\left({10}^{-300}\right)}^{\left(10000 \cdot \left(y + 1\right)\right)}\\ \mathbf{if}\;t_2 = 0:\\ \;\;\;\;1\\ \mathbf{else}:\\ \;\;\;\;\frac{e^{t_2} - 1}{t_2}\\ \end{array} \end{array} \]

FPCore

(FPCore (y)
 :precision binary64
 (let* ((t_0 (sqrt (+ (* y y) 1.0)))
        (t_1 (- (fabs (- y t_0)) (/ 1.0 (+ y t_0))))
        (t_2 (+ (* t_1 t_1) (pow (pow 10.0 -300.0) (* 10000.0 (+ y 1.0))))))
   (if (== t_2 0.0) 1.0 (/ (- (exp t_2) 1.0) t_2))))

C

double code(double y) {
	double t_0 = sqrt(((y * y) + 1.0));
	double t_1 = fabs((y - t_0)) - (1.0 / (y + t_0));
	double t_2 = (t_1 * t_1) + pow(pow(10.0, -300.0), (10000.0 * (y + 1.0)));
	double tmp;
	if (t_2 == 0.0) {
		tmp = 1.0;
	} else {
		tmp = (exp(t_2) - 1.0) / t_2;
	}
	return tmp;
}

Fortran

real(8) function code(y)
    real(8), intent (in) :: y
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_0 = sqrt(((y * y) + 1.0d0))
    t_1 = abs((y - t_0)) - (1.0d0 / (y + t_0))
    t_2 = (t_1 * t_1) + ((10.0d0 ** (-300.0d0)) ** (10000.0d0 * (y + 1.0d0)))
    if (t_2 == 0.0d0) then
        tmp = 1.0d0
    else
        tmp = (exp(t_2) - 1.0d0) / t_2
    end if
    code = tmp
end function

Java

public static double code(double y) {
	double t_0 = Math.sqrt(((y * y) + 1.0));
	double t_1 = Math.abs((y - t_0)) - (1.0 / (y + t_0));
	double t_2 = (t_1 * t_1) + Math.pow(Math.pow(10.0, -300.0), (10000.0 * (y + 1.0)));
	double tmp;
	if (t_2 == 0.0) {
		tmp = 1.0;
	} else {
		tmp = (Math.exp(t_2) - 1.0) / t_2;
	}
	return tmp;
}

Python

def code(y):
	t_0 = math.sqrt(((y * y) + 1.0))
	t_1 = math.fabs((y - t_0)) - (1.0 / (y + t_0))
	t_2 = (t_1 * t_1) + math.pow(math.pow(10.0, -300.0), (10000.0 * (y + 1.0)))
	tmp = 0
	if t_2 == 0.0:
		tmp = 1.0
	else:
		tmp = (math.exp(t_2) - 1.0) / t_2
	return tmp

Julia

function code(y)
	t_0 = sqrt(Float64(Float64(y * y) + 1.0))
	t_1 = Float64(abs(Float64(y - t_0)) - Float64(1.0 / Float64(y + t_0)))
	t_2 = Float64(Float64(t_1 * t_1) + ((10.0 ^ -300.0) ^ Float64(10000.0 * Float64(y + 1.0))))
	tmp = 0.0
	if (t_2 == 0.0)
		tmp = 1.0;
	else
		tmp = Float64(Float64(exp(t_2) - 1.0) / t_2);
	end
	return tmp
end

MATLAB

function tmp_2 = code(y)
	t_0 = sqrt(((y * y) + 1.0));
	t_1 = abs((y - t_0)) - (1.0 / (y + t_0));
	t_2 = (t_1 * t_1) + ((10.0 ^ -300.0) ^ (10000.0 * (y + 1.0)));
	tmp = 0.0;
	if (t_2 == 0.0)
		tmp = 1.0;
	else
		tmp = (exp(t_2) - 1.0) / t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[y_] := Block[{t$95$0 = N[Sqrt[N[(N[(y * y), $MachinePrecision] + 1.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Abs[N[(y - t$95$0), $MachinePrecision]], $MachinePrecision] - N[(1.0 / N[(y + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * t$95$1), $MachinePrecision] + N[Power[N[Power[10.0, -300.0], $MachinePrecision], N[(10000.0 * N[(y + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[Equal[t$95$2, 0.0], 1.0, N[(N[(N[Exp[t$95$2], $MachinePrecision] - 1.0), $MachinePrecision] / t$95$2), $MachinePrecision]]]]]