Exception for Rectangular parallelepiped of dimension a×b×c

• could not determine a ground truth

Specification

Math

\[\begin{array}{l} \\ 2 \cdot \left(\left(1 \cdot \frac{1}{9} + \frac{1}{9} \cdot \frac{1}{9}\right) + \frac{1}{9} \cdot 1\right) \end{array} \]

FPCore

(FPCore ()
 :precision binary64
 (*
  2.0
  (+ (+ (* 1.0 (/ 1.0 9.0)) (* (/ 1.0 9.0) (/ 1.0 9.0))) (* (/ 1.0 9.0) 1.0))))

C

double code() {
	return 2.0 * (((1.0 * (1.0 / 9.0)) + ((1.0 / 9.0) * (1.0 / 9.0))) + ((1.0 / 9.0) * 1.0));
}

Fortran

real(8) function code()
    code = 2.0d0 * (((1.0d0 * (1.0d0 / 9.0d0)) + ((1.0d0 / 9.0d0) * (1.0d0 / 9.0d0))) + ((1.0d0 / 9.0d0) * 1.0d0))
end function

Java

public static double code() {
	return 2.0 * (((1.0 * (1.0 / 9.0)) + ((1.0 / 9.0) * (1.0 / 9.0))) + ((1.0 / 9.0) * 1.0));
}

Python

def code():
	return 2.0 * (((1.0 * (1.0 / 9.0)) + ((1.0 / 9.0) * (1.0 / 9.0))) + ((1.0 / 9.0) * 1.0))

Julia

function code()
	return Float64(2.0 * Float64(Float64(Float64(1.0 * Float64(1.0 / 9.0)) + Float64(Float64(1.0 / 9.0) * Float64(1.0 / 9.0))) + Float64(Float64(1.0 / 9.0) * 1.0)))
end

MATLAB

function tmp = code()
	tmp = 2.0 * (((1.0 * (1.0 / 9.0)) + ((1.0 / 9.0) * (1.0 / 9.0))) + ((1.0 / 9.0) * 1.0));
end

Wolfram

code[] := N[(2.0 * N[(N[(N[(1.0 * N[(1.0 / 9.0), $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 / 9.0), $MachinePrecision] * N[(1.0 / 9.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 / 9.0), $MachinePrecision] * 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]