Diagrams.Solve.Polynomial:cubForm from diagrams-solve-0.1, A

Percentage Accurate: 95.2% → 98.5%

Time: 4.9s

Alternatives: 19

Speedup: 0.9×

• 27.9% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \end{array} \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* (* a 27.0) b)))

C

double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = ((x * 2.0d0) - (((y * 9.0d0) * z) * t)) + ((a * 27.0d0) * b)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Python

def code(x, y, z, t, a, b):
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b)

Julia

function code(x, y, z, t, a, b)
	return Float64(Float64(Float64(x * 2.0) - Float64(Float64(Float64(y * 9.0) * z) * t)) + Float64(Float64(a * 27.0) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b)
	tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Initial Program: 95.2% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \end{array} \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* (* a 27.0) b)))

C

double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = ((x * 2.0d0) - (((y * 9.0d0) * z) * t)) + ((a * 27.0d0) * b)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Python

def code(x, y, z, t, a, b):
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b)

Julia

function code(x, y, z, t, a, b)
	return Float64(Float64(Float64(x * 2.0) - Float64(Float64(Float64(y * 9.0) * z) * t)) + Float64(Float64(a * 27.0) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b)
	tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Alternative 1: 98.5% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq -9.5 \cdot 10^{+45}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot z, t \cdot y, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \left(z \cdot \left(9 \cdot y\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= z -9.5e+45)
   (fma (* -9.0 z) (* t y) (fma (* b a) 27.0 (* 2.0 x)))
   (fma (* b 27.0) a (- (* 2.0 x) (* t (* z (* 9.0 y)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= -9.5e+45) {
		tmp = fma((-9.0 * z), (t * y), fma((b * a), 27.0, (2.0 * x)));
	} else {
		tmp = fma((b * 27.0), a, ((2.0 * x) - (t * (z * (9.0 * y)))));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (z <= -9.5e+45)
		tmp = fma(Float64(-9.0 * z), Float64(t * y), fma(Float64(b * a), 27.0, Float64(2.0 * x)));
	else
		tmp = fma(Float64(b * 27.0), a, Float64(Float64(2.0 * x) - Float64(t * Float64(z * Float64(9.0 * y)))));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[z, -9.5e+45], N[(N[(-9.0 * z), $MachinePrecision] * N[(t * y), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0 + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * 27.0), $MachinePrecision] * a + N[(N[(2.0 * x), $MachinePrecision] - N[(t * N[(z * N[(9.0 * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if z < -9.4999999999999998e45

   1. Initial program 92.1%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\left(2 \cdot x + 27 \cdot \left(a \cdot b\right)\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 99.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9 \cdot z, t \cdot y, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)} \]

   if -9.4999999999999998e45 < z

   1. Initial program 94.7%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b} \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b + \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right)} \]

      3. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b} + \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right)} \cdot b + \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      5. associate-*l* N/A

         \[\leadsto \color{blue}{a \cdot \left(27 \cdot b\right)} + \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      6. *-commutative N/A

         \[\leadsto \color{blue}{\left(27 \cdot b\right) \cdot a} + \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      7. lower-fma.f64 N/A

         \[\leadsto \color{blue}{\mathsf{fma}\left(27 \cdot b, a, x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right)} \]

      8. *-commutative N/A

         \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot 27}, a, x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      9. lower-*.f64 95.7

         \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot 27}, a, x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      10. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{x \cdot 2} - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      11. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      12. lower-*.f64 95.7

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) \]

      13. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right) \cdot t}\right) \]

      14. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{t \cdot \left(\left(y \cdot 9\right) \cdot z\right)}\right) \]

      15. lower-*.f64 95.7

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{t \cdot \left(\left(y \cdot 9\right) \cdot z\right)}\right) \]

      16. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right)}\right) \]

      17. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \color{blue}{\left(z \cdot \left(y \cdot 9\right)\right)}\right) \]

      18. lower-*.f64 95.7

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \color{blue}{\left(z \cdot \left(y \cdot 9\right)\right)}\right) \]

      19. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \left(z \cdot \color{blue}{\left(y \cdot 9\right)}\right)\right) \]

      20. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \left(z \cdot \color{blue}{\left(9 \cdot y\right)}\right)\right) \]

      21. lower-*.f64 95.7

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \left(z \cdot \color{blue}{\left(9 \cdot y\right)}\right)\right) \]

   4. Applied rewrites 95.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - t \cdot \left(z \cdot \left(9 \cdot y\right)\right)\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 2: 87.3% accurate, 0.4× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -4 \cdot 10^{+21}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{elif}\;t\_1 \leq 10^{+115}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+298}:\\ \;\;\;\;\mathsf{fma}\left(z \cdot y, t \cdot -9, b \cdot \left(27 \cdot a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -4e+21)
     (fma -9.0 (* (* z y) t) (* (* b a) 27.0))
     (if (<= t_1 1e+115)
       (fma (* b 27.0) a (* 2.0 x))
       (if (<= t_1 2e+298)
         (fma (* z y) (* t -9.0) (* b (* 27.0 a)))
         (fma (* -9.0 y) (* z t) (* 2.0 x)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_1 <= -4e+21) {
		tmp = fma(-9.0, ((z * y) * t), ((b * a) * 27.0));
	} else if (t_1 <= 1e+115) {
		tmp = fma((b * 27.0), a, (2.0 * x));
	} else if (t_1 <= 2e+298) {
		tmp = fma((z * y), (t * -9.0), (b * (27.0 * a)));
	} else {
		tmp = fma((-9.0 * y), (z * t), (2.0 * x));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_1 <= -4e+21)
		tmp = fma(-9.0, Float64(Float64(z * y) * t), Float64(Float64(b * a) * 27.0));
	elseif (t_1 <= 1e+115)
		tmp = fma(Float64(b * 27.0), a, Float64(2.0 * x));
	elseif (t_1 <= 2e+298)
		tmp = fma(Float64(z * y), Float64(t * -9.0), Float64(b * Float64(27.0 * a)));
	else
		tmp = fma(Float64(-9.0 * y), Float64(z * t), Float64(2.0 * x));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -4e+21], N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 1e+115], N[(N[(b * 27.0), $MachinePrecision] * a + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+298], N[(N[(z * y), $MachinePrecision] * N[(t * -9.0), $MachinePrecision] + N[(b * N[(27.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(-9.0 * y), $MachinePrecision] * N[(z * t), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 4 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4e21

   1. Initial program 92.2%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 81.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)} \]

   if -4e21 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 1e115

   1. Initial program 99.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 90.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 90.8%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
   8. Step-by-step derivation

   9. Applied rewrites 90.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)} \]

   if 1e115 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 1.9999999999999999e298

   1. Initial program 99.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 86.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.0%

      \[\leadsto \mathsf{fma}\left(z \cdot y, \color{blue}{t \cdot -9}, b \cdot \left(27 \cdot a\right)\right) \]

   if 1.9999999999999999e298 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 65.2%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right) \cdot t}\right) + \left(a \cdot 27\right) \cdot b \]

      2. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(y \cdot 9\right)} \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      4. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(y \cdot \left(9 \cdot z\right)\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      6. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \color{blue}{\left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

      9. lower-*.f64 89.8

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

   4. Applied rewrites 89.8%

      \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      2. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right) \cdot y}\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      4. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right) \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(z \cdot \left(9 \cdot t\right)\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      6. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \color{blue}{\left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      9. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

      10. lower-*.f64 89.7

          \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

   6. Applied rewrites 89.7%

      \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   7. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b} \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      3. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right)} \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      5. associate-*l* N/A

         \[\leadsto \color{blue}{a \cdot \left(27 \cdot b\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      6. *-commutative N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      7. lift-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      8. *-commutative N/A

         \[\leadsto \color{blue}{\left(b \cdot 27\right) \cdot a} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      9. lower-fma.f64 96.4

         \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      10. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{x \cdot 2} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      11. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      12. lift-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      13. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) \]

      14. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      15. lower-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      16. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right)} \cdot z\right) \]

      17. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      18. lower-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      19. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(t \cdot 9\right)}\right) \cdot z\right) \]

      20. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

      21. lower-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

   8. Applied rewrites 96.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right)} \]

   9. Taylor expanded in a around 0

      \[\leadsto \color{blue}{2 \cdot x - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   10. Step-by-step derivation

   11. Applied rewrites 93.2%

       \[\leadsto \color{blue}{\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 89.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -4 \cdot 10^{+21}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{elif}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 10^{+115}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \mathbf{elif}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 2 \cdot 10^{+298}:\\ \;\;\;\;\mathsf{fma}\left(z \cdot y, t \cdot -9, b \cdot \left(27 \cdot a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 87.3% accurate, 0.4× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ t_2 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_2 \leq -4 \cdot 10^{+21}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t\_2 \leq 10^{+115}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \mathbf{elif}\;t\_2 \leq 2 \cdot 10^{+298}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (fma -9.0 (* (* z y) t) (* (* b a) 27.0)))
        (t_2 (* (* (* y 9.0) z) t)))
   (if (<= t_2 -4e+21)
     t_1
     (if (<= t_2 1e+115)
       (fma (* b 27.0) a (* 2.0 x))
       (if (<= t_2 2e+298) t_1 (fma (* -9.0 y) (* z t) (* 2.0 x)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = fma(-9.0, ((z * y) * t), ((b * a) * 27.0));
	double t_2 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_2 <= -4e+21) {
		tmp = t_1;
	} else if (t_2 <= 1e+115) {
		tmp = fma((b * 27.0), a, (2.0 * x));
	} else if (t_2 <= 2e+298) {
		tmp = t_1;
	} else {
		tmp = fma((-9.0 * y), (z * t), (2.0 * x));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = fma(-9.0, Float64(Float64(z * y) * t), Float64(Float64(b * a) * 27.0))
	t_2 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_2 <= -4e+21)
		tmp = t_1;
	elseif (t_2 <= 1e+115)
		tmp = fma(Float64(b * 27.0), a, Float64(2.0 * x));
	elseif (t_2 <= 2e+298)
		tmp = t_1;
	else
		tmp = fma(Float64(-9.0 * y), Float64(z * t), Float64(2.0 * x));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$2, -4e+21], t$95$1, If[LessEqual[t$95$2, 1e+115], N[(N[(b * 27.0), $MachinePrecision] * a + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, 2e+298], t$95$1, N[(N[(-9.0 * y), $MachinePrecision] * N[(z * t), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4e21 or 1e115 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 1.9999999999999999e298

   1. Initial program 94.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 83.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)} \]

   if -4e21 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 1e115

   1. Initial program 99.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 90.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 90.8%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
   8. Step-by-step derivation

   9. Applied rewrites 90.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)} \]

   if 1.9999999999999999e298 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 65.2%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right) \cdot t}\right) + \left(a \cdot 27\right) \cdot b \]

      2. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(y \cdot 9\right)} \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      4. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(y \cdot \left(9 \cdot z\right)\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      6. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \color{blue}{\left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

      9. lower-*.f64 89.8

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

   4. Applied rewrites 89.8%

      \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      2. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right) \cdot y}\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      4. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right) \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(z \cdot \left(9 \cdot t\right)\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      6. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \color{blue}{\left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      9. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

      10. lower-*.f64 89.7

          \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

   6. Applied rewrites 89.7%

      \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   7. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b} \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      3. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right)} \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      5. associate-*l* N/A

         \[\leadsto \color{blue}{a \cdot \left(27 \cdot b\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      6. *-commutative N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      7. lift-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      8. *-commutative N/A

         \[\leadsto \color{blue}{\left(b \cdot 27\right) \cdot a} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      9. lower-fma.f64 96.4

         \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      10. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{x \cdot 2} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      11. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      12. lift-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      13. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) \]

      14. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      15. lower-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      16. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right)} \cdot z\right) \]

      17. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      18. lower-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      19. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(t \cdot 9\right)}\right) \cdot z\right) \]

      20. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

      21. lower-*.f64 96.4

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

   8. Applied rewrites 96.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right)} \]

   9. Taylor expanded in a around 0

      \[\leadsto \color{blue}{2 \cdot x - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   10. Step-by-step derivation

   11. Applied rewrites 93.2%

       \[\leadsto \color{blue}{\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 89.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -4 \cdot 10^{+21}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{elif}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 10^{+115}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \mathbf{elif}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 2 \cdot 10^{+298}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 84.5% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+195}:\\ \;\;\;\;\left(\left(-9 \cdot z\right) \cdot t\right) \cdot y\\ \mathbf{elif}\;t\_1 \leq 10^{+166}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -5e+195)
     (* (* (* -9.0 z) t) y)
     (if (<= t_1 1e+166)
       (fma (* b 27.0) a (* 2.0 x))
       (fma (* -9.0 y) (* z t) (* 2.0 x))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_1 <= -5e+195) {
		tmp = ((-9.0 * z) * t) * y;
	} else if (t_1 <= 1e+166) {
		tmp = fma((b * 27.0), a, (2.0 * x));
	} else {
		tmp = fma((-9.0 * y), (z * t), (2.0 * x));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_1 <= -5e+195)
		tmp = Float64(Float64(Float64(-9.0 * z) * t) * y);
	elseif (t_1 <= 1e+166)
		tmp = fma(Float64(b * 27.0), a, Float64(2.0 * x));
	else
		tmp = fma(Float64(-9.0 * y), Float64(z * t), Float64(2.0 * x));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -5e+195], N[(N[(N[(-9.0 * z), $MachinePrecision] * t), $MachinePrecision] * y), $MachinePrecision], If[LessEqual[t$95$1, 1e+166], N[(N[(b * 27.0), $MachinePrecision] * a + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], N[(N[(-9.0 * y), $MachinePrecision] * N[(z * t), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.9999999999999998e195

   1. Initial program 86.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 75.7%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 75.8%

      \[\leadsto \left(\left(-9 \cdot z\right) \cdot t\right) \cdot \color{blue}{y} \]

   if -4.9999999999999998e195 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.4%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
   8. Step-by-step derivation

   9. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)} \]

   if 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 77.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right) \cdot t}\right) + \left(a \cdot 27\right) \cdot b \]

      2. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(y \cdot 9\right)} \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      4. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(y \cdot \left(9 \cdot z\right)\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      6. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \color{blue}{\left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

      9. lower-*.f64 81.3

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

   4. Applied rewrites 81.3%

      \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      2. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right) \cdot y}\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      4. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right) \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(z \cdot \left(9 \cdot t\right)\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      6. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \color{blue}{\left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      9. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

      10. lower-*.f64 85.3

          \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

   6. Applied rewrites 85.3%

      \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   7. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b} \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      3. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right)} \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      5. associate-*l* N/A

         \[\leadsto \color{blue}{a \cdot \left(27 \cdot b\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      6. *-commutative N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      7. lift-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      8. *-commutative N/A

         \[\leadsto \color{blue}{\left(b \cdot 27\right) \cdot a} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      9. lower-fma.f64 89.5

         \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      10. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{x \cdot 2} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      11. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      12. lift-*.f64 89.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      13. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) \]

      14. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      15. lower-*.f64 89.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      16. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right)} \cdot z\right) \]

      17. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      18. lower-*.f64 89.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      19. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(t \cdot 9\right)}\right) \cdot z\right) \]

      20. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

      21. lower-*.f64 89.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

   8. Applied rewrites 89.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right)} \]

   9. Taylor expanded in a around 0

      \[\leadsto \color{blue}{2 \cdot x - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   10. Step-by-step derivation

   11. Applied rewrites 81.4%

       \[\leadsto \color{blue}{\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 85.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -5 \cdot 10^{+195}:\\ \;\;\;\;\left(\left(-9 \cdot z\right) \cdot t\right) \cdot y\\ \mathbf{elif}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 10^{+166}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 83.9% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+195} \lor \neg \left(t\_1 \leq 10^{+166}\right):\\ \;\;\;\;\left(\left(-9 \cdot z\right) \cdot t\right) \cdot y\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (or (<= t_1 -5e+195) (not (<= t_1 1e+166)))
     (* (* (* -9.0 z) t) y)
     (fma (* b 27.0) a (* 2.0 x)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if ((t_1 <= -5e+195) || !(t_1 <= 1e+166)) {
		tmp = ((-9.0 * z) * t) * y;
	} else {
		tmp = fma((b * 27.0), a, (2.0 * x));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if ((t_1 <= -5e+195) || !(t_1 <= 1e+166))
		tmp = Float64(Float64(Float64(-9.0 * z) * t) * y);
	else
		tmp = fma(Float64(b * 27.0), a, Float64(2.0 * x));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -5e+195], N[Not[LessEqual[t$95$1, 1e+166]], $MachinePrecision]], N[(N[(N[(-9.0 * z), $MachinePrecision] * t), $MachinePrecision] * y), $MachinePrecision], N[(N[(b * 27.0), $MachinePrecision] * a + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.9999999999999998e195 or 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 81.0%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 74.4%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 78.1%

      \[\leadsto \left(\left(-9 \cdot z\right) \cdot t\right) \cdot \color{blue}{y} \]

   if -4.9999999999999998e195 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.4%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
   8. Step-by-step derivation

   9. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 84.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -5 \cdot 10^{+195} \lor \neg \left(\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 10^{+166}\right):\\ \;\;\;\;\left(\left(-9 \cdot z\right) \cdot t\right) \cdot y\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 83.9% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+195} \lor \neg \left(t\_1 \leq 10^{+166}\right):\\ \;\;\;\;\left(\left(-9 \cdot z\right) \cdot t\right) \cdot y\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (or (<= t_1 -5e+195) (not (<= t_1 1e+166)))
     (* (* (* -9.0 z) t) y)
     (+ (fma (* b 27.0) a x) x))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if ((t_1 <= -5e+195) || !(t_1 <= 1e+166)) {
		tmp = ((-9.0 * z) * t) * y;
	} else {
		tmp = fma((b * 27.0), a, x) + x;
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if ((t_1 <= -5e+195) || !(t_1 <= 1e+166))
		tmp = Float64(Float64(Float64(-9.0 * z) * t) * y);
	else
		tmp = Float64(fma(Float64(b * 27.0), a, x) + x);
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -5e+195], N[Not[LessEqual[t$95$1, 1e+166]], $MachinePrecision]], N[(N[(N[(-9.0 * z), $MachinePrecision] * t), $MachinePrecision] * y), $MachinePrecision], N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.9999999999999998e195 or 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 81.0%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 74.4%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 78.1%

      \[\leadsto \left(\left(-9 \cdot z\right) \cdot t\right) \cdot \color{blue}{y} \]

   if -4.9999999999999998e195 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.4%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
3. Recombined 2 regimes into one program.

4. Final simplification 84.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -5 \cdot 10^{+195} \lor \neg \left(\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 10^{+166}\right):\\ \;\;\;\;\left(\left(-9 \cdot z\right) \cdot t\right) \cdot y\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 82.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -1 \cdot 10^{+295} \lor \neg \left(t\_1 \leq 10^{+166}\right):\\ \;\;\;\;-9 \cdot \left(z \cdot \left(y \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (or (<= t_1 -1e+295) (not (<= t_1 1e+166)))
     (* -9.0 (* z (* y t)))
     (+ (fma (* b 27.0) a x) x))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if ((t_1 <= -1e+295) || !(t_1 <= 1e+166)) {
		tmp = -9.0 * (z * (y * t));
	} else {
		tmp = fma((b * 27.0), a, x) + x;
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if ((t_1 <= -1e+295) || !(t_1 <= 1e+166))
		tmp = Float64(-9.0 * Float64(z * Float64(y * t)));
	else
		tmp = Float64(fma(Float64(b * 27.0), a, x) + x);
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -1e+295], N[Not[LessEqual[t$95$1, 1e+166]], $MachinePrecision]], N[(-9.0 * N[(z * N[(y * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -9.9999999999999998e294 or 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 78.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 76.0%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 79.9%

      \[\leadsto -9 \cdot \left(z \cdot \color{blue}{\left(y \cdot t\right)}\right) \]

   if -9.9999999999999998e294 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 85.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 85.3%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
3. Recombined 2 regimes into one program.

4. Final simplification 83.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -1 \cdot 10^{+295} \lor \neg \left(\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 10^{+166}\right):\\ \;\;\;\;-9 \cdot \left(z \cdot \left(y \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 83.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+195}:\\ \;\;\;\;\left(-9 \cdot \left(y \cdot z\right)\right) \cdot t\\ \mathbf{elif}\;t\_1 \leq 10^{+166}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot t\right) \cdot \left(-9 \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -5e+195)
     (* (* -9.0 (* y z)) t)
     (if (<= t_1 1e+166) (+ (fma (* b 27.0) a x) x) (* (* y t) (* -9.0 z))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_1 <= -5e+195) {
		tmp = (-9.0 * (y * z)) * t;
	} else if (t_1 <= 1e+166) {
		tmp = fma((b * 27.0), a, x) + x;
	} else {
		tmp = (y * t) * (-9.0 * z);
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_1 <= -5e+195)
		tmp = Float64(Float64(-9.0 * Float64(y * z)) * t);
	elseif (t_1 <= 1e+166)
		tmp = Float64(fma(Float64(b * 27.0), a, x) + x);
	else
		tmp = Float64(Float64(y * t) * Float64(-9.0 * z));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -5e+195], N[(N[(-9.0 * N[(y * z), $MachinePrecision]), $MachinePrecision] * t), $MachinePrecision], If[LessEqual[t$95$1, 1e+166], N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision], N[(N[(y * t), $MachinePrecision] * N[(-9.0 * z), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.9999999999999998e195

   1. Initial program 86.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 75.7%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 75.7%

      \[\leadsto \left(-9 \cdot \left(y \cdot z\right)\right) \cdot \color{blue}{t} \]

   if -4.9999999999999998e195 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.4%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]

   if 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 77.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 73.6%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 77.3%

      \[\leadsto \left(y \cdot t\right) \cdot \color{blue}{\left(-9 \cdot z\right)} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 9: 83.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+195}:\\ \;\;\;\;\left(-9 \cdot \left(y \cdot z\right)\right) \cdot t\\ \mathbf{elif}\;t\_1 \leq 10^{+166}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(z \cdot \left(y \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -5e+195)
     (* (* -9.0 (* y z)) t)
     (if (<= t_1 1e+166) (+ (fma (* b 27.0) a x) x) (* -9.0 (* z (* y t)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_1 <= -5e+195) {
		tmp = (-9.0 * (y * z)) * t;
	} else if (t_1 <= 1e+166) {
		tmp = fma((b * 27.0), a, x) + x;
	} else {
		tmp = -9.0 * (z * (y * t));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_1 <= -5e+195)
		tmp = Float64(Float64(-9.0 * Float64(y * z)) * t);
	elseif (t_1 <= 1e+166)
		tmp = Float64(fma(Float64(b * 27.0), a, x) + x);
	else
		tmp = Float64(-9.0 * Float64(z * Float64(y * t)));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -5e+195], N[(N[(-9.0 * N[(y * z), $MachinePrecision]), $MachinePrecision] * t), $MachinePrecision], If[LessEqual[t$95$1, 1e+166], N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision], N[(-9.0 * N[(z * N[(y * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.9999999999999998e195

   1. Initial program 86.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 75.7%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 75.7%

      \[\leadsto \left(-9 \cdot \left(y \cdot z\right)\right) \cdot \color{blue}{t} \]

   if -4.9999999999999998e195 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.4%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]

   if 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 77.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 73.6%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 77.2%

      \[\leadsto -9 \cdot \left(z \cdot \color{blue}{\left(y \cdot t\right)}\right) \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 10: 83.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+195}:\\ \;\;\;\;-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)\\ \mathbf{elif}\;t\_1 \leq 10^{+166}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(z \cdot \left(y \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -5e+195)
     (* -9.0 (* (* z y) t))
     (if (<= t_1 1e+166) (+ (fma (* b 27.0) a x) x) (* -9.0 (* z (* y t)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_1 <= -5e+195) {
		tmp = -9.0 * ((z * y) * t);
	} else if (t_1 <= 1e+166) {
		tmp = fma((b * 27.0), a, x) + x;
	} else {
		tmp = -9.0 * (z * (y * t));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_1 <= -5e+195)
		tmp = Float64(-9.0 * Float64(Float64(z * y) * t));
	elseif (t_1 <= 1e+166)
		tmp = Float64(fma(Float64(b * 27.0), a, x) + x);
	else
		tmp = Float64(-9.0 * Float64(z * Float64(y * t)));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -5e+195], N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 1e+166], N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision], N[(-9.0 * N[(z * N[(y * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.9999999999999998e195

   1. Initial program 86.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 75.7%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]

   if -4.9999999999999998e195 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999994e165

   1. Initial program 99.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 87.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 87.4%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]

   if 9.9999999999999994e165 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 77.6%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 73.6%

      \[\leadsto \color{blue}{-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 77.2%

      \[\leadsto -9 \cdot \left(z \cdot \color{blue}{\left(y \cdot t\right)}\right) \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 11: 83.2% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -1 \cdot 10^{+29}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot t\right) \cdot y, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{elif}\;t\_1 \leq 10^{+103}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (<= t_1 -1e+29)
     (fma -9.0 (* (* z t) y) (* (* b a) 27.0))
     (if (<= t_1 1e+103)
       (fma (* -9.0 y) (* z t) (* 2.0 x))
       (+ (fma (* b 27.0) a x) x)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if (t_1 <= -1e+29) {
		tmp = fma(-9.0, ((z * t) * y), ((b * a) * 27.0));
	} else if (t_1 <= 1e+103) {
		tmp = fma((-9.0 * y), (z * t), (2.0 * x));
	} else {
		tmp = fma((b * 27.0), a, x) + x;
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(a * 27.0) * b)
	tmp = 0.0
	if (t_1 <= -1e+29)
		tmp = fma(-9.0, Float64(Float64(z * t) * y), Float64(Float64(b * a) * 27.0));
	elseif (t_1 <= 1e+103)
		tmp = fma(Float64(-9.0 * y), Float64(z * t), Float64(2.0 * x));
	else
		tmp = Float64(fma(Float64(b * 27.0), a, x) + x);
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]}, If[LessEqual[t$95$1, -1e+29], N[(-9.0 * N[(N[(z * t), $MachinePrecision] * y), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 1e+103], N[(N[(-9.0 * y), $MachinePrecision] * N[(z * t), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -9.99999999999999914e28

   1. Initial program 96.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 91.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 90.4%

      \[\leadsto \mathsf{fma}\left(-9, \left(z \cdot t\right) \cdot \color{blue}{y}, \left(b \cdot a\right) \cdot 27\right) \]

   if -9.99999999999999914e28 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 1e103

   1. Initial program 94.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right) \cdot t}\right) + \left(a \cdot 27\right) \cdot b \]

      2. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(y \cdot 9\right)} \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      4. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(y \cdot \left(9 \cdot z\right)\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      6. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \color{blue}{\left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

      9. lower-*.f64 93.4

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

   4. Applied rewrites 93.4%

      \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      2. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right) \cdot y}\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      4. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right) \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(z \cdot \left(9 \cdot t\right)\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      6. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \color{blue}{\left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      9. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

      10. lower-*.f64 94.5

          \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

   6. Applied rewrites 94.5%

      \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   7. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b} \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      3. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right)} \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      5. associate-*l* N/A

         \[\leadsto \color{blue}{a \cdot \left(27 \cdot b\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      6. *-commutative N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      7. lift-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      8. *-commutative N/A

         \[\leadsto \color{blue}{\left(b \cdot 27\right) \cdot a} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      9. lower-fma.f64 94.5

         \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      10. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{x \cdot 2} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      11. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      12. lift-*.f64 94.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      13. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) \]

      14. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      15. lower-*.f64 94.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      16. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right)} \cdot z\right) \]

      17. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      18. lower-*.f64 94.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      19. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(t \cdot 9\right)}\right) \cdot z\right) \]

      20. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

      21. lower-*.f64 94.5

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

   8. Applied rewrites 94.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right)} \]

   9. Taylor expanded in a around 0

      \[\leadsto \color{blue}{2 \cdot x - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   10. Step-by-step derivation

   11. Applied rewrites 82.5%

       \[\leadsto \color{blue}{\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)} \]

   if 1e103 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 89.7%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 95.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 95.7%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
3. Recombined 3 regimes into one program.

4. Final simplification 86.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(a \cdot 27\right) \cdot b \leq -1 \cdot 10^{+29}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot t\right) \cdot y, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{elif}\;\left(a \cdot 27\right) \cdot b \leq 10^{+103}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot y, z \cdot t, 2 \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, x\right) + x\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 93.2% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -2 \cdot 10^{+131}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot 27, a, \left(x + x\right) - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= (* (* (* y 9.0) z) t) -2e+131)
   (fma -9.0 (* (* z y) t) (* (* b a) 27.0))
   (fma (* b 27.0) a (- (+ x x) (* (* y (* 9.0 t)) z)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((((y * 9.0) * z) * t) <= -2e+131) {
		tmp = fma(-9.0, ((z * y) * t), ((b * a) * 27.0));
	} else {
		tmp = fma((b * 27.0), a, ((x + x) - ((y * (9.0 * t)) * z)));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (Float64(Float64(Float64(y * 9.0) * z) * t) <= -2e+131)
		tmp = fma(-9.0, Float64(Float64(z * y) * t), Float64(Float64(b * a) * 27.0));
	else
		tmp = fma(Float64(b * 27.0), a, Float64(Float64(x + x) - Float64(Float64(y * Float64(9.0 * t)) * z)));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision], -2e+131], N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision]), $MachinePrecision], N[(N[(b * 27.0), $MachinePrecision] * a + N[(N[(x + x), $MachinePrecision] - N[(N[(y * N[(9.0 * t), $MachinePrecision]), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -1.9999999999999998e131

   1. Initial program 88.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 85.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)} \]

   if -1.9999999999999998e131 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 94.9%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right) \cdot t}\right) + \left(a \cdot 27\right) \cdot b \]

      2. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(y \cdot 9\right) \cdot z\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(y \cdot 9\right)} \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      4. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(y \cdot \left(9 \cdot z\right)\right)} \cdot t\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      6. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \color{blue}{\left(\left(9 \cdot z\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

      9. lower-*.f64 93.4

         \[\leadsto \left(x \cdot 2 - y \cdot \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right)\right) + \left(a \cdot 27\right) \cdot b \]

   4. Applied rewrites 93.4%

      \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{y \cdot \left(\left(z \cdot 9\right) \cdot t\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      2. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right) \cdot y}\right) + \left(a \cdot 27\right) \cdot b \]

      3. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(\left(z \cdot 9\right) \cdot t\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      4. lift-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \left(\color{blue}{\left(z \cdot 9\right)} \cdot t\right) \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      5. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{\left(z \cdot \left(9 \cdot t\right)\right)} \cdot y\right) + \left(a \cdot 27\right) \cdot b \]

      6. associate-*l* N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      7. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      8. lower-*.f64 N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \color{blue}{\left(\left(9 \cdot t\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]

      9. *-commutative N/A

         \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

      10. lower-*.f64 96.2

          \[\leadsto \left(x \cdot 2 - z \cdot \left(\color{blue}{\left(t \cdot 9\right)} \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b \]

   6. Applied rewrites 96.2%

      \[\leadsto \left(x \cdot 2 - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) + \left(a \cdot 27\right) \cdot b \]
   7. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \color{blue}{\left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) + \left(a \cdot 27\right) \cdot b} \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      3. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right) \cdot b} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \color{blue}{\left(a \cdot 27\right)} \cdot b + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      5. associate-*l* N/A

         \[\leadsto \color{blue}{a \cdot \left(27 \cdot b\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      6. *-commutative N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      7. lift-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(b \cdot 27\right)} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      8. *-commutative N/A

         \[\leadsto \color{blue}{\left(b \cdot 27\right) \cdot a} + \left(x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      9. lower-fma.f64 97.2

         \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, x \cdot 2 - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right)} \]

      10. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{x \cdot 2} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      11. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      12. lift-*.f64 97.2

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - z \cdot \left(\left(t \cdot 9\right) \cdot y\right)\right) \]

      13. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{z \cdot \left(\left(t \cdot 9\right) \cdot y\right)}\right) \]

      14. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      15. lower-*.f64 97.2

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right) \cdot z}\right) \]

      16. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(\left(t \cdot 9\right) \cdot y\right)} \cdot z\right) \]

      17. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      18. lower-*.f64 97.2

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \color{blue}{\left(y \cdot \left(t \cdot 9\right)\right)} \cdot z\right) \]

      19. lift-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(t \cdot 9\right)}\right) \cdot z\right) \]

      20. *-commutative N/A

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

      21. lower-*.f64 97.2

          \[\leadsto \mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \color{blue}{\left(9 \cdot t\right)}\right) \cdot z\right) \]

   8. Applied rewrites 97.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot 27, a, 2 \cdot x - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right)} \]
   9. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{2 \cdot x} - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right) \]

      2. count-2-rev N/A

         \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{\left(x + x\right)} - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right) \]

      3. lift-+.f64 97.2

         \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{\left(x + x\right)} - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right) \]

   10. Applied rewrites 97.2%

       \[\leadsto \mathsf{fma}\left(b \cdot 27, a, \color{blue}{\left(x + x\right)} - \left(y \cdot \left(9 \cdot t\right)\right) \cdot z\right) \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 13: 93.2% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -2 \cdot 10^{+131}:\\ \;\;\;\;\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot z, t \cdot y, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= (* (* (* y 9.0) z) t) -2e+131)
   (fma -9.0 (* (* z y) t) (* (* b a) 27.0))
   (fma (* -9.0 z) (* t y) (fma (* b a) 27.0 (* 2.0 x)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((((y * 9.0) * z) * t) <= -2e+131) {
		tmp = fma(-9.0, ((z * y) * t), ((b * a) * 27.0));
	} else {
		tmp = fma((-9.0 * z), (t * y), fma((b * a), 27.0, (2.0 * x)));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (Float64(Float64(Float64(y * 9.0) * z) * t) <= -2e+131)
		tmp = fma(-9.0, Float64(Float64(z * y) * t), Float64(Float64(b * a) * 27.0));
	else
		tmp = fma(Float64(-9.0 * z), Float64(t * y), fma(Float64(b * a), 27.0, Float64(2.0 * x)));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision], -2e+131], N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision]), $MachinePrecision], N[(N[(-9.0 * z), $MachinePrecision] * N[(t * y), $MachinePrecision] + N[(N[(b * a), $MachinePrecision] * 27.0 + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -1.9999999999999998e131

   1. Initial program 88.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 85.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9, \left(z \cdot y\right) \cdot t, \left(b \cdot a\right) \cdot 27\right)} \]

   if -1.9999999999999998e131 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 94.9%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\left(2 \cdot x + 27 \cdot \left(a \cdot b\right)\right) - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 96.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(-9 \cdot z, t \cdot y, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 14: 53.9% accurate, 0.8× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -2 \cdot 10^{+16} \lor \neg \left(t\_1 \leq 50000000\right):\\ \;\;\;\;\left(b \cdot a\right) \cdot 27 + x\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (or (<= t_1 -2e+16) (not (<= t_1 50000000.0)))
     (+ (* (* b a) 27.0) x)
     (+ x x))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if ((t_1 <= -2e+16) || !(t_1 <= 50000000.0)) {
		tmp = ((b * a) * 27.0) + x;
	} else {
		tmp = x + x;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (a * 27.0d0) * b
    if ((t_1 <= (-2d+16)) .or. (.not. (t_1 <= 50000000.0d0))) then
        tmp = ((b * a) * 27.0d0) + x
    else
        tmp = x + x
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if ((t_1 <= -2e+16) || !(t_1 <= 50000000.0)) {
		tmp = ((b * a) * 27.0) + x;
	} else {
		tmp = x + x;
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = (a * 27.0) * b
	tmp = 0
	if (t_1 <= -2e+16) or not (t_1 <= 50000000.0):
		tmp = ((b * a) * 27.0) + x
	else:
		tmp = x + x
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(a * 27.0) * b)
	tmp = 0.0
	if ((t_1 <= -2e+16) || !(t_1 <= 50000000.0))
		tmp = Float64(Float64(Float64(b * a) * 27.0) + x);
	else
		tmp = Float64(x + x);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = (a * 27.0) * b;
	tmp = 0.0;
	if ((t_1 <= -2e+16) || ~((t_1 <= 50000000.0)))
		tmp = ((b * a) * 27.0) + x;
	else
		tmp = x + x;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -2e+16], N[Not[LessEqual[t$95$1, 50000000.0]], $MachinePrecision]], N[(N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision] + x), $MachinePrecision], N[(x + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -2e16 or 5e7 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 94.0%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0

      \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 83.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
   6. Step-by-step derivation

   7. Applied rewrites 83.0%

      \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]

   8. Taylor expanded in x around 0

      \[\leadsto 27 \cdot \left(a \cdot b\right) + x \]
   9. Step-by-step derivation

   10. Applied rewrites 74.1%

       \[\leadsto \left(b \cdot a\right) \cdot 27 + x \]

   if -2e16 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 5e7

   1. Initial program 94.1%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{2 \cdot x} \]
   4. Step-by-step derivation

   5. Applied rewrites 43.7%

      \[\leadsto \color{blue}{2 \cdot x} \]
   6. Step-by-step derivation

   7. Applied rewrites 43.7%

      \[\leadsto x + \color{blue}{x} \]
3. Recombined 2 regimes into one program.

4. Final simplification 60.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(a \cdot 27\right) \cdot b \leq -2 \cdot 10^{+16} \lor \neg \left(\left(a \cdot 27\right) \cdot b \leq 50000000\right):\\ \;\;\;\;\left(b \cdot a\right) \cdot 27 + x\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 52.6% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -2 \cdot 10^{+16} \lor \neg \left(t\_1 \leq 5 \cdot 10^{+81}\right):\\ \;\;\;\;\left(27 \cdot b\right) \cdot a\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (or (<= t_1 -2e+16) (not (<= t_1 5e+81))) (* (* 27.0 b) a) (+ x x))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if ((t_1 <= -2e+16) || !(t_1 <= 5e+81)) {
		tmp = (27.0 * b) * a;
	} else {
		tmp = x + x;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (a * 27.0d0) * b
    if ((t_1 <= (-2d+16)) .or. (.not. (t_1 <= 5d+81))) then
        tmp = (27.0d0 * b) * a
    else
        tmp = x + x
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if ((t_1 <= -2e+16) || !(t_1 <= 5e+81)) {
		tmp = (27.0 * b) * a;
	} else {
		tmp = x + x;
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = (a * 27.0) * b
	tmp = 0
	if (t_1 <= -2e+16) or not (t_1 <= 5e+81):
		tmp = (27.0 * b) * a
	else:
		tmp = x + x
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(a * 27.0) * b)
	tmp = 0.0
	if ((t_1 <= -2e+16) || !(t_1 <= 5e+81))
		tmp = Float64(Float64(27.0 * b) * a);
	else
		tmp = Float64(x + x);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = (a * 27.0) * b;
	tmp = 0.0;
	if ((t_1 <= -2e+16) || ~((t_1 <= 5e+81)))
		tmp = (27.0 * b) * a;
	else
		tmp = x + x;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -2e+16], N[Not[LessEqual[t$95$1, 5e+81]], $MachinePrecision]], N[(N[(27.0 * b), $MachinePrecision] * a), $MachinePrecision], N[(x + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -2e16 or 4.9999999999999998e81 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 93.3%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 77.5%

      \[\leadsto \color{blue}{\left(b \cdot a\right) \cdot 27} \]
   6. Step-by-step derivation

   7. Applied rewrites 77.5%

      \[\leadsto \left(27 \cdot b\right) \cdot \color{blue}{a} \]

   if -2e16 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 4.9999999999999998e81

   1. Initial program 94.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{2 \cdot x} \]
   4. Step-by-step derivation

   5. Applied rewrites 42.5%

      \[\leadsto \color{blue}{2 \cdot x} \]
   6. Step-by-step derivation

   7. Applied rewrites 42.5%

      \[\leadsto x + \color{blue}{x} \]
3. Recombined 2 regimes into one program.

4. Final simplification 59.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(a \cdot 27\right) \cdot b \leq -2 \cdot 10^{+16} \lor \neg \left(\left(a \cdot 27\right) \cdot b \leq 5 \cdot 10^{+81}\right):\\ \;\;\;\;\left(27 \cdot b\right) \cdot a\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 52.6% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -2 \cdot 10^{+16}:\\ \;\;\;\;\left(b \cdot a\right) \cdot 27\\ \mathbf{elif}\;t\_1 \leq 5 \cdot 10^{+81}:\\ \;\;\;\;x + x\\ \mathbf{else}:\\ \;\;\;\;\left(27 \cdot b\right) \cdot a\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (<= t_1 -2e+16)
     (* (* b a) 27.0)
     (if (<= t_1 5e+81) (+ x x) (* (* 27.0 b) a)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if (t_1 <= -2e+16) {
		tmp = (b * a) * 27.0;
	} else if (t_1 <= 5e+81) {
		tmp = x + x;
	} else {
		tmp = (27.0 * b) * a;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (a * 27.0d0) * b
    if (t_1 <= (-2d+16)) then
        tmp = (b * a) * 27.0d0
    else if (t_1 <= 5d+81) then
        tmp = x + x
    else
        tmp = (27.0d0 * b) * a
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (a * 27.0) * b;
	double tmp;
	if (t_1 <= -2e+16) {
		tmp = (b * a) * 27.0;
	} else if (t_1 <= 5e+81) {
		tmp = x + x;
	} else {
		tmp = (27.0 * b) * a;
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = (a * 27.0) * b
	tmp = 0
	if t_1 <= -2e+16:
		tmp = (b * a) * 27.0
	elif t_1 <= 5e+81:
		tmp = x + x
	else:
		tmp = (27.0 * b) * a
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(a * 27.0) * b)
	tmp = 0.0
	if (t_1 <= -2e+16)
		tmp = Float64(Float64(b * a) * 27.0);
	elseif (t_1 <= 5e+81)
		tmp = Float64(x + x);
	else
		tmp = Float64(Float64(27.0 * b) * a);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = (a * 27.0) * b;
	tmp = 0.0;
	if (t_1 <= -2e+16)
		tmp = (b * a) * 27.0;
	elseif (t_1 <= 5e+81)
		tmp = x + x;
	else
		tmp = (27.0 * b) * a;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]}, If[LessEqual[t$95$1, -2e+16], N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision], If[LessEqual[t$95$1, 5e+81], N[(x + x), $MachinePrecision], N[(N[(27.0 * b), $MachinePrecision] * a), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -2e16

   1. Initial program 95.5%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 73.5%

      \[\leadsto \color{blue}{\left(b \cdot a\right) \cdot 27} \]

   if -2e16 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 4.9999999999999998e81

   1. Initial program 94.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{2 \cdot x} \]
   4. Step-by-step derivation

   5. Applied rewrites 42.5%

      \[\leadsto \color{blue}{2 \cdot x} \]
   6. Step-by-step derivation

   7. Applied rewrites 42.5%

      \[\leadsto x + \color{blue}{x} \]

   if 4.9999999999999998e81 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 90.3%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{27 \cdot \left(a \cdot b\right)} \]
   4. Step-by-step derivation

   5. Applied rewrites 82.8%

      \[\leadsto \color{blue}{\left(b \cdot a\right) \cdot 27} \]
   6. Step-by-step derivation

   7. Applied rewrites 82.8%

      \[\leadsto \left(27 \cdot b\right) \cdot \color{blue}{a} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 17: 64.4% accurate, 2.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \mathsf{fma}\left(b \cdot 27, a, x\right) + x \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b) :precision binary64 (+ (fma (* b 27.0) a x) x))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	return fma((b * 27.0), a, x) + x;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	return Float64(fma(Float64(b * 27.0), a, x) + x)
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(b * 27.0), $MachinePrecision] * a + x), $MachinePrecision] + x), $MachinePrecision]

Derivation

1. Initial program 94.1%

   \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
2. Add Preprocessing

3. Taylor expanded in y around 0

   \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
4. Step-by-step derivation

5. Applied rewrites 67.7%

   \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
6. Step-by-step derivation

7. Applied rewrites 67.7%

   \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
8. Add Preprocessing

Alternative 18: 64.4% accurate, 2.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \mathsf{fma}\left(27 \cdot a, b, x\right) + x \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b) :precision binary64 (+ (fma (* 27.0 a) b x) x))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	return fma((27.0 * a), b, x) + x;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	return Float64(fma(Float64(27.0 * a), b, x) + x)
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(27.0 * a), $MachinePrecision] * b + x), $MachinePrecision] + x), $MachinePrecision]

Derivation

1. Initial program 94.1%

   \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
2. Add Preprocessing

3. Taylor expanded in y around 0

   \[\leadsto \color{blue}{2 \cdot x + 27 \cdot \left(a \cdot b\right)} \]
4. Step-by-step derivation

5. Applied rewrites 67.7%

   \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)} \]
6. Step-by-step derivation

7. Applied rewrites 67.7%

   \[\leadsto \mathsf{fma}\left(b \cdot 27, a, x\right) + \color{blue}{x} \]
8. Step-by-step derivation

9. Applied rewrites 67.7%

   \[\leadsto \mathsf{fma}\left(27 \cdot a, b, x\right) + x \]
10. Add Preprocessing

Alternative 19: 30.4% accurate, 9.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\\\ [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ x + x \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b) :precision binary64 (+ x x))

C

assert(x < y && y < z && z < t && t < a && a < b);
assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	return x + x;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = x + x
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	return x + x;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	return x + x

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	return Float64(x + x)
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp = code(x, y, z, t, a, b)
	tmp = x + x;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := N[(x + x), $MachinePrecision]

Derivation

1. Initial program 94.1%

   \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
2. Add Preprocessing

3. Taylor expanded in x around inf

   \[\leadsto \color{blue}{2 \cdot x} \]
4. Step-by-step derivation

5. Applied rewrites 27.2%

   \[\leadsto \color{blue}{2 \cdot x} \]
6. Step-by-step derivation

7. Applied rewrites 27.2%

   \[\leadsto x + \color{blue}{x} \]
8. Add Preprocessing

Developer Target 1: 94.9% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y < 7.590524218811189 \cdot 10^{-161}:\\ \;\;\;\;\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + a \cdot \left(27 \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;\left(x \cdot 2 - 9 \cdot \left(y \cdot \left(t \cdot z\right)\right)\right) + \left(a \cdot 27\right) \cdot b\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (if (< y 7.590524218811189e-161)
   (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* a (* 27.0 b)))
   (+ (- (* x 2.0) (* 9.0 (* y (* t z)))) (* (* a 27.0) b))))

C

double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (y < 7.590524218811189e-161) {
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b));
	} else {
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b);
	}
	return tmp;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z, t, a, b)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: tmp
    if (y < 7.590524218811189d-161) then
        tmp = ((x * 2.0d0) - (((y * 9.0d0) * z) * t)) + (a * (27.0d0 * b))
    else
        tmp = ((x * 2.0d0) - (9.0d0 * (y * (t * z)))) + ((a * 27.0d0) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (y < 7.590524218811189e-161) {
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b));
	} else {
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b):
	tmp = 0
	if y < 7.590524218811189e-161:
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b))
	else:
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b)
	return tmp

Julia

function code(x, y, z, t, a, b)
	tmp = 0.0
	if (y < 7.590524218811189e-161)
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(Float64(Float64(y * 9.0) * z) * t)) + Float64(a * Float64(27.0 * b)));
	else
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(t * z)))) + Float64(Float64(a * 27.0) * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (y < 7.590524218811189e-161)
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b));
	else
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := If[Less[y, 7.590524218811189e-161], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]

Reproduce

herbie shell --seed 2025018 
(FPCore (x y z t a b)
  :name "Diagrams.Solve.Polynomial:cubForm  from diagrams-solve-0.1, A"
  :precision binary64

  :alt
  (! :herbie-platform default (if (< y 7590524218811189/100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (+ (- (* x 2) (* (* (* y 9) z) t)) (* a (* 27 b))) (+ (- (* x 2) (* 9 (* y (* t z)))) (* (* a 27) b))))

  (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* (* a 27.0) b)))