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

Percentage Accurate: 95.6% → 97.5%

Time: 9.2s

Alternatives: 14

Speedup: 0.9×

• 27.2% 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: 95.6% 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: 97.5% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq -1.6 \cdot 10^{+75}:\\ \;\;\;\;\mathsf{fma}\left(y \cdot \left(t \cdot z\right), -9, x + x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot \left(z \cdot y\right), t, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= z -1.6e+75)
   (fma (* y (* t z)) -9.0 (+ x x))
   (fma (* -9.0 (* z y)) t (fma (* b a) 27.0 (* 2.0 x)))))

C

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 <= -1.6e+75) {
		tmp = fma((y * (t * z)), -9.0, (x + x));
	} else {
		tmp = fma((-9.0 * (z * y)), t, fma((b * a), 27.0, (2.0 * x)));
	}
	return tmp;
}

Julia

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 <= -1.6e+75)
		tmp = fma(Float64(y * Float64(t * z)), -9.0, Float64(x + x));
	else
		tmp = fma(Float64(-9.0 * Float64(z * y)), t, 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.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[z, -1.6e+75], N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0 + N[(x + x), $MachinePrecision]), $MachinePrecision], N[(N[(-9.0 * N[(z * y), $MachinePrecision]), $MachinePrecision] * t + N[(N[(b * a), $MachinePrecision] * 27.0 + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if z < -1.59999999999999992e75

   1. Initial program 84.5%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 17.9

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 17.9%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 78.6

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

   8. Applied rewrites 78.6%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 78.6

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

   10. Applied rewrites 78.6%

       \[\leadsto \mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right) \]
   11. Step-by-step derivation

       1. lift-*.f64 N/A

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

       2. lift-*.f64 N/A

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

       3. associate-*l* N/A

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

       4. *-commutative N/A

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

       5. lower-*.f64 N/A

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

       6. lower-*.f64 79.0

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

   12. Applied rewrites 79.0%

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

   if -1.59999999999999992e75 < z

   1. Initial program 95.7%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   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. lift--.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. fp-cancel-sub-sign-inv N/A

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

      5. lift-*.f64 N/A

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

      6. *-commutative N/A

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

      7. lift-*.f64 N/A

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

      8. lift-*.f64 N/A

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

      9. *-commutative N/A

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

      10. associate-*r* N/A

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

      11. associate-+l+ N/A

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

   4. Applied rewrites 96.6%

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

Alternative 2: 85.7% accurate, 0.4× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \mathsf{fma}\left(y \cdot \left(t \cdot z\right), -9, x + x\right)\\ t_2 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_2 \leq -\infty:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t\_2 \leq -5 \cdot 10^{-27}:\\ \;\;\;\;\mathsf{fma}\left(\left(z \cdot y\right) \cdot -9, t, x\right) + x\\ \mathbf{elif}\;t\_2 \leq 5 \cdot 10^{+117}:\\ \;\;\;\;\mathsf{fma}\left(a, 27 \cdot b, x \cdot 2\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

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 (* y (* t z)) -9.0 (+ x x))) (t_2 (* (* (* y 9.0) z) t)))
   (if (<= t_2 (- INFINITY))
     t_1
     (if (<= t_2 -5e-27)
       (+ (fma (* (* z y) -9.0) t x) x)
       (if (<= t_2 5e+117) (fma a (* 27.0 b) (* x 2.0)) t_1)))))

C

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((y * (t * z)), -9.0, (x + x));
	double t_2 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_2 <= -((double) INFINITY)) {
		tmp = t_1;
	} else if (t_2 <= -5e-27) {
		tmp = fma(((z * y) * -9.0), t, x) + x;
	} else if (t_2 <= 5e+117) {
		tmp = fma(a, (27.0 * b), (x * 2.0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = fma(Float64(y * Float64(t * z)), -9.0, Float64(x + x))
	t_2 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_2 <= Float64(-Inf))
		tmp = t_1;
	elseif (t_2 <= -5e-27)
		tmp = Float64(fma(Float64(Float64(z * y) * -9.0), t, x) + x);
	elseif (t_2 <= 5e+117)
		tmp = fma(a, Float64(27.0 * b), Float64(x * 2.0));
	else
		tmp = t_1;
	end
	return tmp
end

Wolfram

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[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0 + N[(x + x), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$2, (-Infinity)], t$95$1, If[LessEqual[t$95$2, -5e-27], N[(N[(N[(N[(z * y), $MachinePrecision] * -9.0), $MachinePrecision] * t + x), $MachinePrecision] + x), $MachinePrecision], If[LessEqual[t$95$2, 5e+117], N[(a * N[(27.0 * b), $MachinePrecision] + N[(x * 2.0), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -inf.0 or 4.99999999999999983e117 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 79.7%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 12.0

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 12.0%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 82.4

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

   8. Applied rewrites 82.4%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 82.4

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

   10. Applied rewrites 82.4%

       \[\leadsto \mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right) \]
   11. Step-by-step derivation

       1. lift-*.f64 N/A

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

       2. lift-*.f64 N/A

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

       3. associate-*l* N/A

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

       4. *-commutative N/A

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

       5. lower-*.f64 N/A

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

       6. lower-*.f64 94.9

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

   12. Applied rewrites 94.9%

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

   if -inf.0 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -5.0000000000000002e-27

   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 x around inf

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

      1. lower-*.f64 31.6

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 31.6%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 82.2

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

   8. Applied rewrites 82.2%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 82.2

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

   10. Applied rewrites 82.2%

       \[\leadsto \mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right) \]
   11. Step-by-step derivation

       1. lift-+.f64 N/A

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

       2. lift-fma.f64 N/A

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

       3. lift-*.f64 N/A

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

       4. associate-+r+ N/A

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

       5. lower-+.f64 N/A

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

       6. lift-*.f64 N/A

          \[\leadsto \left(\left(\left(y \cdot z\right) \cdot t\right) \cdot -9 + x\right) + x \]

       7. lift-*.f64 N/A

          \[\leadsto \left(\left(\left(y \cdot z\right) \cdot t\right) \cdot -9 + x\right) + x \]

       8. lift-*.f64 N/A

          \[\leadsto \left(\left(\left(y \cdot z\right) \cdot t\right) \cdot -9 + x\right) + x \]

       9. associate-*l* N/A

          \[\leadsto \left(\left(y \cdot z\right) \cdot \left(t \cdot -9\right) + x\right) + x \]

       10. *-commutative N/A

           \[\leadsto \left(\left(y \cdot z\right) \cdot \left(-9 \cdot t\right) + x\right) + x \]

       11. *-commutative N/A

           \[\leadsto \left(\left(z \cdot y\right) \cdot \left(-9 \cdot t\right) + x\right) + x \]

       12. associate-*r* N/A

           \[\leadsto \left(\left(\left(z \cdot y\right) \cdot -9\right) \cdot t + x\right) + x \]

       13. *-commutative N/A

           \[\leadsto \left(\left(\left(y \cdot z\right) \cdot -9\right) \cdot t + x\right) + x \]

       14. *-commutative N/A

           \[\leadsto \left(\left(-9 \cdot \left(y \cdot z\right)\right) \cdot t + x\right) + x \]

       15. lower-fma.f64 N/A

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

       16. *-commutative N/A

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

       17. lower-*.f64 N/A

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

       18. *-commutative N/A

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

       19. lift-*.f64 82.2

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

   12. Applied rewrites 82.2%

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

   if -5.0000000000000002e-27 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 4.99999999999999983e117

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 95.0

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

   5. Applied rewrites 95.0%

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

      1. lift-*.f64 N/A

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

      2. lift-fma.f64 N/A

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

      3. lift-*.f64 N/A

         \[\leadsto \left(b \cdot a\right) \cdot 27 + 2 \cdot x \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

         \[\leadsto b \cdot \left(27 \cdot a\right) + 2 \cdot x \]

      6. *-commutative N/A

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

      7. *-commutative N/A

         \[\leadsto \left(a \cdot 27\right) \cdot b + 2 \cdot x \]

      8. associate-*l* N/A

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

      9. lower-fma.f64 N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 94.9

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

   7. Applied rewrites 94.9%

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

Alternative 3: 84.8% accurate, 0.4× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \mathsf{fma}\left(\left(z \cdot y\right) \cdot -9, t, x\right) + x\\ t_2 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_2 \leq -5 \cdot 10^{-27}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t\_2 \leq 4 \cdot 10^{-20}:\\ \;\;\;\;\mathsf{fma}\left(a, 27 \cdot b, x \cdot 2\right)\\ \mathbf{elif}\;t\_2 \leq 10^{+291}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot \left(t \cdot z\right)\right) \cdot -9\\ \end{array} \end{array} \]

FPCore

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 (* (* z y) -9.0) t x) x)) (t_2 (* (* (* y 9.0) z) t)))
   (if (<= t_2 -5e-27)
     t_1
     (if (<= t_2 4e-20)
       (fma a (* 27.0 b) (* x 2.0))
       (if (<= t_2 1e+291) t_1 (* (* y (* t z)) -9.0))))))

C

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(((z * y) * -9.0), t, x) + x;
	double t_2 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_2 <= -5e-27) {
		tmp = t_1;
	} else if (t_2 <= 4e-20) {
		tmp = fma(a, (27.0 * b), (x * 2.0));
	} else if (t_2 <= 1e+291) {
		tmp = t_1;
	} else {
		tmp = (y * (t * z)) * -9.0;
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(fma(Float64(Float64(z * y) * -9.0), t, x) + x)
	t_2 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_2 <= -5e-27)
		tmp = t_1;
	elseif (t_2 <= 4e-20)
		tmp = fma(a, Float64(27.0 * b), Float64(x * 2.0));
	elseif (t_2 <= 1e+291)
		tmp = t_1;
	else
		tmp = Float64(Float64(y * Float64(t * z)) * -9.0);
	end
	return tmp
end

Wolfram

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[(N[(z * y), $MachinePrecision] * -9.0), $MachinePrecision] * t + x), $MachinePrecision] + x), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$2, -5e-27], t$95$1, If[LessEqual[t$95$2, 4e-20], N[(a * N[(27.0 * b), $MachinePrecision] + N[(x * 2.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, 1e+291], t$95$1, N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0), $MachinePrecision]]]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -5.0000000000000002e-27 or 3.99999999999999978e-20 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 9.9999999999999996e290

   1. Initial program 92.6%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 23.3

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 23.3%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 82.7

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

   8. Applied rewrites 82.7%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 82.7

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

   10. Applied rewrites 82.7%

       \[\leadsto \mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right) \]
   11. Step-by-step derivation

       1. lift-+.f64 N/A

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

       2. lift-fma.f64 N/A

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

       3. lift-*.f64 N/A

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

       4. associate-+r+ N/A

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

       5. lower-+.f64 N/A

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

       6. lift-*.f64 N/A

          \[\leadsto \left(\left(\left(y \cdot z\right) \cdot t\right) \cdot -9 + x\right) + x \]

       7. lift-*.f64 N/A

          \[\leadsto \left(\left(\left(y \cdot z\right) \cdot t\right) \cdot -9 + x\right) + x \]

       8. lift-*.f64 N/A

          \[\leadsto \left(\left(\left(y \cdot z\right) \cdot t\right) \cdot -9 + x\right) + x \]

       9. associate-*l* N/A

          \[\leadsto \left(\left(y \cdot z\right) \cdot \left(t \cdot -9\right) + x\right) + x \]

       10. *-commutative N/A

           \[\leadsto \left(\left(y \cdot z\right) \cdot \left(-9 \cdot t\right) + x\right) + x \]

       11. *-commutative N/A

           \[\leadsto \left(\left(z \cdot y\right) \cdot \left(-9 \cdot t\right) + x\right) + x \]

       12. associate-*r* N/A

           \[\leadsto \left(\left(\left(z \cdot y\right) \cdot -9\right) \cdot t + x\right) + x \]

       13. *-commutative N/A

           \[\leadsto \left(\left(\left(y \cdot z\right) \cdot -9\right) \cdot t + x\right) + x \]

       14. *-commutative N/A

           \[\leadsto \left(\left(-9 \cdot \left(y \cdot z\right)\right) \cdot t + x\right) + x \]

       15. lower-fma.f64 N/A

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

       16. *-commutative N/A

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

       17. lower-*.f64 N/A

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

       18. *-commutative N/A

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

       19. lift-*.f64 81.7

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

   12. Applied rewrites 81.7%

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

   if -5.0000000000000002e-27 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 3.99999999999999978e-20

   1. Initial program 99.2%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 98.0

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

   5. Applied rewrites 98.0%

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

      1. lift-*.f64 N/A

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

      2. lift-fma.f64 N/A

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

      3. lift-*.f64 N/A

         \[\leadsto \left(b \cdot a\right) \cdot 27 + 2 \cdot x \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

         \[\leadsto b \cdot \left(27 \cdot a\right) + 2 \cdot x \]

      6. *-commutative N/A

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

      7. *-commutative N/A

         \[\leadsto \left(a \cdot 27\right) \cdot b + 2 \cdot x \]

      8. associate-*l* N/A

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

      9. lower-fma.f64 N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 98.0

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

   7. Applied rewrites 98.0%

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

   if 9.9999999999999996e290 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 69.1%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 14.6

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 14.6%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in y around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. lower-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      5. lower-*.f64 69.2

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

   8. Applied rewrites 69.2%

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

      1. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      2. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      3. associate-*l* N/A

         \[\leadsto \left(y \cdot \left(z \cdot t\right)\right) \cdot -9 \]

      4. *-commutative N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      5. lower-*.f64 N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      6. lower-*.f64 88.2

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

   10. Applied rewrites 88.2%

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

Alternative 4: 84.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{-27}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot t, z \cdot y, 2 \cdot x\right)\\ \mathbf{elif}\;t\_1 \leq 5 \cdot 10^{+117}:\\ \;\;\;\;\mathsf{fma}\left(a, 27 \cdot b, x \cdot 2\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y \cdot \left(t \cdot z\right), -9, x + x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -5e-27)
     (fma (* -9.0 t) (* z y) (* 2.0 x))
     (if (<= t_1 5e+117)
       (fma a (* 27.0 b) (* x 2.0))
       (fma (* y (* t z)) -9.0 (+ x x))))))

C

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-27) {
		tmp = fma((-9.0 * t), (z * y), (2.0 * x));
	} else if (t_1 <= 5e+117) {
		tmp = fma(a, (27.0 * b), (x * 2.0));
	} else {
		tmp = fma((y * (t * z)), -9.0, (x + x));
	}
	return tmp;
}

Julia

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-27)
		tmp = fma(Float64(-9.0 * t), Float64(z * y), Float64(2.0 * x));
	elseif (t_1 <= 5e+117)
		tmp = fma(a, Float64(27.0 * b), Float64(x * 2.0));
	else
		tmp = fma(Float64(y * Float64(t * z)), -9.0, Float64(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.
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-27], N[(N[(-9.0 * t), $MachinePrecision] * N[(z * y), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 5e+117], N[(a * N[(27.0 * b), $MachinePrecision] + N[(x * 2.0), $MachinePrecision]), $MachinePrecision], N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0 + N[(x + x), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -5.0000000000000002e-27

   1. Initial program 89.3%

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

   3. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. associate-*r* N/A

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

      5. lower-fma.f64 N/A

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

      6. lower-*.f64 N/A

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

      7. *-commutative N/A

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

      8. lower-*.f64 N/A

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

      9. lower-*.f64 81.4

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

   5. Applied rewrites 81.4%

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

   if -5.0000000000000002e-27 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 4.99999999999999983e117

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 95.0

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

   5. Applied rewrites 95.0%

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

      1. lift-*.f64 N/A

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

      2. lift-fma.f64 N/A

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

      3. lift-*.f64 N/A

         \[\leadsto \left(b \cdot a\right) \cdot 27 + 2 \cdot x \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

         \[\leadsto b \cdot \left(27 \cdot a\right) + 2 \cdot x \]

      6. *-commutative N/A

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

      7. *-commutative N/A

         \[\leadsto \left(a \cdot 27\right) \cdot b + 2 \cdot x \]

      8. associate-*l* N/A

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

      9. lower-fma.f64 N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 94.9

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

   7. Applied rewrites 94.9%

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

   if 4.99999999999999983e117 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 81.4%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 19.8

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 19.8%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 83.9

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

   8. Applied rewrites 83.9%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 83.9

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

   10. Applied rewrites 83.9%

       \[\leadsto \mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right) \]
   11. Step-by-step derivation

       1. lift-*.f64 N/A

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

       2. lift-*.f64 N/A

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

       3. associate-*l* N/A

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

       4. *-commutative N/A

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

       5. lower-*.f64 N/A

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

       6. lower-*.f64 93.3

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

   12. Applied rewrites 93.3%

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

Alternative 5: 84.5% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{-27}:\\ \;\;\;\;\mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right)\\ \mathbf{elif}\;t\_1 \leq 5 \cdot 10^{+117}:\\ \;\;\;\;\mathsf{fma}\left(a, 27 \cdot b, x \cdot 2\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y \cdot \left(t \cdot z\right), -9, x + x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -5e-27)
     (fma (* (* y z) t) -9.0 (+ x x))
     (if (<= t_1 5e+117)
       (fma a (* 27.0 b) (* x 2.0))
       (fma (* y (* t z)) -9.0 (+ x x))))))

C

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-27) {
		tmp = fma(((y * z) * t), -9.0, (x + x));
	} else if (t_1 <= 5e+117) {
		tmp = fma(a, (27.0 * b), (x * 2.0));
	} else {
		tmp = fma((y * (t * z)), -9.0, (x + x));
	}
	return tmp;
}

Julia

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-27)
		tmp = fma(Float64(Float64(y * z) * t), -9.0, Float64(x + x));
	elseif (t_1 <= 5e+117)
		tmp = fma(a, Float64(27.0 * b), Float64(x * 2.0));
	else
		tmp = fma(Float64(y * Float64(t * z)), -9.0, Float64(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.
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-27], N[(N[(N[(y * z), $MachinePrecision] * t), $MachinePrecision] * -9.0 + N[(x + x), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 5e+117], N[(a * N[(27.0 * b), $MachinePrecision] + N[(x * 2.0), $MachinePrecision]), $MachinePrecision], N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0 + N[(x + x), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -5.0000000000000002e-27

   1. Initial program 89.3%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 17.7

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 17.7%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 81.4

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

   8. Applied rewrites 81.4%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 81.4

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

   10. Applied rewrites 81.4%

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

   if -5.0000000000000002e-27 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 4.99999999999999983e117

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 95.0

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

   5. Applied rewrites 95.0%

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

      1. lift-*.f64 N/A

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

      2. lift-fma.f64 N/A

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

      3. lift-*.f64 N/A

         \[\leadsto \left(b \cdot a\right) \cdot 27 + 2 \cdot x \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

         \[\leadsto b \cdot \left(27 \cdot a\right) + 2 \cdot x \]

      6. *-commutative N/A

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

      7. *-commutative N/A

         \[\leadsto \left(a \cdot 27\right) \cdot b + 2 \cdot x \]

      8. associate-*l* N/A

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

      9. lower-fma.f64 N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 94.9

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

   7. Applied rewrites 94.9%

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

   if 4.99999999999999983e117 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 81.4%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 19.8

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 19.8%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in a around 0

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

      1. fp-cancel-sub-sign-inv N/A

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

      2. metadata-eval N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lower-fma.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 83.9

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

   8. Applied rewrites 83.9%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 83.9

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

   10. Applied rewrites 83.9%

       \[\leadsto \mathsf{fma}\left(\left(y \cdot z\right) \cdot t, -9, x + x\right) \]
   11. Step-by-step derivation

       1. lift-*.f64 N/A

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

       2. lift-*.f64 N/A

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

       3. associate-*l* N/A

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

       4. *-commutative N/A

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

       5. lower-*.f64 N/A

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

       6. lower-*.f64 93.3

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

   12. Applied rewrites 93.3%

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

Alternative 6: 82.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+193}:\\ \;\;\;\;\left(z \cdot y\right) \cdot \left(-9 \cdot t\right)\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+176}:\\ \;\;\;\;\mathsf{fma}\left(a, 27 \cdot b, x \cdot 2\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot \left(t \cdot z\right)\right) \cdot -9\\ \end{array} \end{array} \]

FPCore

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+193)
     (* (* z y) (* -9.0 t))
     (if (<= t_1 2e+176)
       (fma a (* 27.0 b) (* x 2.0))
       (* (* y (* t z)) -9.0)))))

C

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+193) {
		tmp = (z * y) * (-9.0 * t);
	} else if (t_1 <= 2e+176) {
		tmp = fma(a, (27.0 * b), (x * 2.0));
	} else {
		tmp = (y * (t * z)) * -9.0;
	}
	return tmp;
}

Julia

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+193)
		tmp = Float64(Float64(z * y) * Float64(-9.0 * t));
	elseif (t_1 <= 2e+176)
		tmp = fma(a, Float64(27.0 * b), Float64(x * 2.0));
	else
		tmp = Float64(Float64(y * Float64(t * z)) * -9.0);
	end
	return tmp
end

Wolfram

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+193], N[(N[(z * y), $MachinePrecision] * N[(-9.0 * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+176], N[(a * N[(27.0 * b), $MachinePrecision] + N[(x * 2.0), $MachinePrecision]), $MachinePrecision], N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.99999999999999972e193

   1. Initial program 82.2%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 4.7

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 4.7%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in y around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. lower-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      5. lower-*.f64 82.3

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

   8. Applied rewrites 82.3%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      3. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

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

      6. lower-*.f64 N/A

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

      7. *-commutative N/A

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

      8. lift-*.f64 N/A

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

      9. lift-*.f64 82.3

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

   10. Applied rewrites 82.3%

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

   if -4.99999999999999972e193 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 2e176

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 88.0

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

   5. Applied rewrites 88.0%

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

      1. lift-*.f64 N/A

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

      2. lift-fma.f64 N/A

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

      3. lift-*.f64 N/A

         \[\leadsto \left(b \cdot a\right) \cdot 27 + 2 \cdot x \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

         \[\leadsto b \cdot \left(27 \cdot a\right) + 2 \cdot x \]

      6. *-commutative N/A

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

      7. *-commutative N/A

         \[\leadsto \left(a \cdot 27\right) \cdot b + 2 \cdot x \]

      8. associate-*l* N/A

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

      9. lower-fma.f64 N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 88.0

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

   7. Applied rewrites 88.0%

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

   if 2e176 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 78.3%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 13.7

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 13.7%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in y around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. lower-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      5. lower-*.f64 75.9

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

   8. Applied rewrites 75.9%

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

      1. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      2. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      3. associate-*l* N/A

         \[\leadsto \left(y \cdot \left(z \cdot t\right)\right) \cdot -9 \]

      4. *-commutative N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      5. lower-*.f64 N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      6. lower-*.f64 81.4

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

   10. Applied rewrites 81.4%

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

Alternative 7: 82.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+193} \lor \neg \left(t\_1 \leq 2 \cdot 10^{+176}\right):\\ \;\;\;\;-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (or (<= t_1 -5e+193) (not (<= t_1 2e+176)))
     (* -9.0 (* (* z y) t))
     (fma (* b a) 27.0 (+ x x)))))

C

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+193) || !(t_1 <= 2e+176)) {
		tmp = -9.0 * ((z * y) * t);
	} else {
		tmp = fma((b * a), 27.0, (x + x));
	}
	return tmp;
}

Julia

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+193) || !(t_1 <= 2e+176))
		tmp = Float64(-9.0 * Float64(Float64(z * y) * t));
	else
		tmp = fma(Float64(b * a), 27.0, Float64(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.
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+193], N[Not[LessEqual[t$95$1, 2e+176]], $MachinePrecision]], N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision], N[(N[(b * a), $MachinePrecision] * 27.0 + N[(x + x), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.99999999999999972e193 or 2e176 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 80.5%

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

   3. Taylor expanded in y around inf

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

      1. lower-*.f64 N/A

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

      2. *-commutative N/A

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

      3. lower-*.f64 N/A

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

      4. *-commutative N/A

         \[\leadsto -9 \cdot \left(\left(z \cdot y\right) \cdot t\right) \]

      5. lower-*.f64 79.4

         \[\leadsto -9 \cdot \left(\left(z \cdot y\right) \cdot t\right) \]

   5. Applied rewrites 79.4%

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

   if -4.99999999999999972e193 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 2e176

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 88.0

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

   5. Applied rewrites 88.0%

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

      1. lift-*.f64 N/A

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

      2. count-2-rev N/A

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

      3. lower-+.f64 88.0

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

   7. Applied rewrites 88.0%

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

4. Final simplification 85.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -5 \cdot 10^{+193} \lor \neg \left(\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 2 \cdot 10^{+176}\right):\\ \;\;\;\;-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 82.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+193}:\\ \;\;\;\;\left(z \cdot y\right) \cdot \left(-9 \cdot t\right)\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+176}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot \left(t \cdot z\right)\right) \cdot -9\\ \end{array} \end{array} \]

FPCore

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+193)
     (* (* z y) (* -9.0 t))
     (if (<= t_1 2e+176) (fma (* b a) 27.0 (+ x x)) (* (* y (* t z)) -9.0)))))

C

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+193) {
		tmp = (z * y) * (-9.0 * t);
	} else if (t_1 <= 2e+176) {
		tmp = fma((b * a), 27.0, (x + x));
	} else {
		tmp = (y * (t * z)) * -9.0;
	}
	return tmp;
}

Julia

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+193)
		tmp = Float64(Float64(z * y) * Float64(-9.0 * t));
	elseif (t_1 <= 2e+176)
		tmp = fma(Float64(b * a), 27.0, Float64(x + x));
	else
		tmp = Float64(Float64(y * Float64(t * z)) * -9.0);
	end
	return tmp
end

Wolfram

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+193], N[(N[(z * y), $MachinePrecision] * N[(-9.0 * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+176], N[(N[(b * a), $MachinePrecision] * 27.0 + N[(x + x), $MachinePrecision]), $MachinePrecision], N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.99999999999999972e193

   1. Initial program 82.2%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 4.7

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 4.7%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in y around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. lower-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      5. lower-*.f64 82.3

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

   8. Applied rewrites 82.3%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      3. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. associate-*l* N/A

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

      5. *-commutative N/A

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

      6. lower-*.f64 N/A

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

      7. *-commutative N/A

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

      8. lift-*.f64 N/A

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

      9. lift-*.f64 82.3

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

   10. Applied rewrites 82.3%

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

   if -4.99999999999999972e193 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 2e176

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 88.0

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

   5. Applied rewrites 88.0%

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

      1. lift-*.f64 N/A

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

      2. count-2-rev N/A

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

      3. lower-+.f64 88.0

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

   7. Applied rewrites 88.0%

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

   if 2e176 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 78.3%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 13.7

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 13.7%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in y around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. lower-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      5. lower-*.f64 75.9

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

   8. Applied rewrites 75.9%

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

      1. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      2. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      3. associate-*l* N/A

         \[\leadsto \left(y \cdot \left(z \cdot t\right)\right) \cdot -9 \]

      4. *-commutative N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      5. lower-*.f64 N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      6. lower-*.f64 81.4

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

   10. Applied rewrites 81.4%

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

Alternative 9: 82.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+193}:\\ \;\;\;\;-9 \cdot \left(\left(z \cdot y\right) \cdot t\right)\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+176}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot \left(t \cdot z\right)\right) \cdot -9\\ \end{array} \end{array} \]

FPCore

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+193)
     (* -9.0 (* (* z y) t))
     (if (<= t_1 2e+176) (fma (* b a) 27.0 (+ x x)) (* (* y (* t z)) -9.0)))))

C

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+193) {
		tmp = -9.0 * ((z * y) * t);
	} else if (t_1 <= 2e+176) {
		tmp = fma((b * a), 27.0, (x + x));
	} else {
		tmp = (y * (t * z)) * -9.0;
	}
	return tmp;
}

Julia

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+193)
		tmp = Float64(-9.0 * Float64(Float64(z * y) * t));
	elseif (t_1 <= 2e+176)
		tmp = fma(Float64(b * a), 27.0, Float64(x + x));
	else
		tmp = Float64(Float64(y * Float64(t * z)) * -9.0);
	end
	return tmp
end

Wolfram

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+193], N[(-9.0 * N[(N[(z * y), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+176], N[(N[(b * a), $MachinePrecision] * 27.0 + N[(x + x), $MachinePrecision]), $MachinePrecision], N[(N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision] * -9.0), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -4.99999999999999972e193

   1. Initial program 82.2%

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

   3. Taylor expanded in y around inf

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

      1. lower-*.f64 N/A

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

      2. *-commutative N/A

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

      3. lower-*.f64 N/A

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

      4. *-commutative N/A

         \[\leadsto -9 \cdot \left(\left(z \cdot y\right) \cdot t\right) \]

      5. lower-*.f64 82.3

         \[\leadsto -9 \cdot \left(\left(z \cdot y\right) \cdot t\right) \]

   5. Applied rewrites 82.3%

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

   if -4.99999999999999972e193 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 2e176

   1. Initial program 99.3%

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

   3. Taylor expanded in y around 0

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

      1. +-commutative N/A

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

      2. *-commutative N/A

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

      3. lower-fma.f64 N/A

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

      4. *-commutative N/A

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

      5. lower-*.f64 N/A

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

      6. lower-*.f64 88.0

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

   5. Applied rewrites 88.0%

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

      1. lift-*.f64 N/A

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

      2. count-2-rev N/A

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

      3. lower-+.f64 88.0

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

   7. Applied rewrites 88.0%

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

   if 2e176 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 78.3%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 13.7

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 13.7%

      \[\leadsto \color{blue}{2 \cdot x} \]

   6. Taylor expanded in y around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      4. lower-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      5. lower-*.f64 75.9

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

   8. Applied rewrites 75.9%

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

      1. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      2. lift-*.f64 N/A

         \[\leadsto \left(\left(y \cdot z\right) \cdot t\right) \cdot -9 \]

      3. associate-*l* N/A

         \[\leadsto \left(y \cdot \left(z \cdot t\right)\right) \cdot -9 \]

      4. *-commutative N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      5. lower-*.f64 N/A

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

      6. lower-*.f64 81.4

         \[\leadsto \left(y \cdot \left(t \cdot z\right)\right) \cdot -9 \]

   10. Applied rewrites 81.4%

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

Alternative 10: 52.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -2 \cdot 10^{+19} \lor \neg \left(t\_1 \leq 2 \cdot 10^{+41}\right):\\ \;\;\;\;\left(27 \cdot a\right) \cdot b\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (or (<= t_1 -2e+19) (not (<= t_1 2e+41))) (* (* 27.0 a) b) (+ x x))))

C

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+19) || !(t_1 <= 2e+41)) {
		tmp = (27.0 * a) * b;
	} 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.
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+19)) .or. (.not. (t_1 <= 2d+41))) then
        tmp = (27.0d0 * a) * b
    else
        tmp = x + x
    end if
    code = tmp
end function

Java

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+19) || !(t_1 <= 2e+41)) {
		tmp = (27.0 * a) * b;
	} else {
		tmp = x + x;
	}
	return tmp;
}

Python

[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+19) or not (t_1 <= 2e+41):
		tmp = (27.0 * a) * b
	else:
		tmp = x + x
	return tmp

Julia

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+19) || !(t_1 <= 2e+41))
		tmp = Float64(Float64(27.0 * a) * b);
	else
		tmp = Float64(x + x);
	end
	return tmp
end

MATLAB

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+19) || ~((t_1 <= 2e+41)))
		tmp = (27.0 * a) * b;
	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.
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+19], N[Not[LessEqual[t$95$1, 2e+41]], $MachinePrecision]], N[(N[(27.0 * a), $MachinePrecision] * b), $MachinePrecision], N[(x + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -2e19 or 2.00000000000000001e41 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 96.2%

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

   3. Taylor expanded in a around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

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

      4. lower-*.f64 62.1

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

   5. Applied rewrites 62.1%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. associate-*l* N/A

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

      4. *-commutative N/A

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

      5. *-commutative N/A

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

      6. lower-*.f64 N/A

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

      7. lower-*.f64 62.2

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

   7. Applied rewrites 62.2%

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

   if -2e19 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 2.00000000000000001e41

   1. Initial program 91.7%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 52.4

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 52.4%

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

      1. lift-*.f64 N/A

         \[\leadsto 2 \cdot \color{blue}{x} \]

      2. count-2-rev N/A

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

      3. lower-+.f64 52.4

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

   7. Applied rewrites 52.4%

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

4. Final simplification 56.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(a \cdot 27\right) \cdot b \leq -2 \cdot 10^{+19} \lor \neg \left(\left(a \cdot 27\right) \cdot b \leq 2 \cdot 10^{+41}\right):\\ \;\;\;\;\left(27 \cdot a\right) \cdot b\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 52.9% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -2 \cdot 10^{+19}:\\ \;\;\;\;\left(b \cdot a\right) \cdot 27\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+41}:\\ \;\;\;\;x + x\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot 27\right) \cdot a\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (<= t_1 -2e+19)
     (* (* b a) 27.0)
     (if (<= t_1 2e+41) (+ x x) (* (* b 27.0) a)))))

C

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+19) {
		tmp = (b * a) * 27.0;
	} else if (t_1 <= 2e+41) {
		tmp = x + x;
	} else {
		tmp = (b * 27.0) * a;
	}
	return tmp;
}

Fortran

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+19)) then
        tmp = (b * a) * 27.0d0
    else if (t_1 <= 2d+41) then
        tmp = x + x
    else
        tmp = (b * 27.0d0) * a
    end if
    code = tmp
end function

Java

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+19) {
		tmp = (b * a) * 27.0;
	} else if (t_1 <= 2e+41) {
		tmp = x + x;
	} else {
		tmp = (b * 27.0) * a;
	}
	return tmp;
}

Python

[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+19:
		tmp = (b * a) * 27.0
	elif t_1 <= 2e+41:
		tmp = x + x
	else:
		tmp = (b * 27.0) * a
	return tmp

Julia

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+19)
		tmp = Float64(Float64(b * a) * 27.0);
	elseif (t_1 <= 2e+41)
		tmp = Float64(x + x);
	else
		tmp = Float64(Float64(b * 27.0) * a);
	end
	return tmp
end

MATLAB

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+19)
		tmp = (b * a) * 27.0;
	elseif (t_1 <= 2e+41)
		tmp = x + x;
	else
		tmp = (b * 27.0) * 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.
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+19], N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision], If[LessEqual[t$95$1, 2e+41], N[(x + x), $MachinePrecision], N[(N[(b * 27.0), $MachinePrecision] * a), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -2e19

   1. Initial program 98.2%

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

   3. Taylor expanded in a around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

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

      4. lower-*.f64 64.0

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

   5. Applied rewrites 64.0%

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

   if -2e19 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 2.00000000000000001e41

   1. Initial program 91.7%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 52.4

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 52.4%

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

      1. lift-*.f64 N/A

         \[\leadsto 2 \cdot \color{blue}{x} \]

      2. count-2-rev N/A

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

      3. lower-+.f64 52.4

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

   7. Applied rewrites 52.4%

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

   if 2.00000000000000001e41 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 92.8%

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

   3. Taylor expanded in a around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

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

      4. lower-*.f64 59.2

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

   5. Applied rewrites 59.2%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. associate-*l* N/A

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

      4. *-commutative N/A

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

      5. *-commutative N/A

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

      6. *-commutative N/A

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

      7. associate-*r* N/A

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

      8. *-commutative N/A

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

      9. lower-*.f64 N/A

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

      10. *-commutative N/A

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

      11. lower-*.f64 59.2

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

   7. Applied rewrites 59.2%

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

Alternative 12: 52.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -2 \cdot 10^{+19}:\\ \;\;\;\;\left(27 \cdot a\right) \cdot b\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+41}:\\ \;\;\;\;x + x\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot 27\right) \cdot a\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* a 27.0) b)))
   (if (<= t_1 -2e+19)
     (* (* 27.0 a) b)
     (if (<= t_1 2e+41) (+ x x) (* (* b 27.0) a)))))

C

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+19) {
		tmp = (27.0 * a) * b;
	} else if (t_1 <= 2e+41) {
		tmp = x + x;
	} else {
		tmp = (b * 27.0) * a;
	}
	return tmp;
}

Fortran

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+19)) then
        tmp = (27.0d0 * a) * b
    else if (t_1 <= 2d+41) then
        tmp = x + x
    else
        tmp = (b * 27.0d0) * a
    end if
    code = tmp
end function

Java

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+19) {
		tmp = (27.0 * a) * b;
	} else if (t_1 <= 2e+41) {
		tmp = x + x;
	} else {
		tmp = (b * 27.0) * a;
	}
	return tmp;
}

Python

[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+19:
		tmp = (27.0 * a) * b
	elif t_1 <= 2e+41:
		tmp = x + x
	else:
		tmp = (b * 27.0) * a
	return tmp

Julia

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+19)
		tmp = Float64(Float64(27.0 * a) * b);
	elseif (t_1 <= 2e+41)
		tmp = Float64(x + x);
	else
		tmp = Float64(Float64(b * 27.0) * a);
	end
	return tmp
end

MATLAB

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+19)
		tmp = (27.0 * a) * b;
	elseif (t_1 <= 2e+41)
		tmp = x + x;
	else
		tmp = (b * 27.0) * 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.
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+19], N[(N[(27.0 * a), $MachinePrecision] * b), $MachinePrecision], If[LessEqual[t$95$1, 2e+41], N[(x + x), $MachinePrecision], N[(N[(b * 27.0), $MachinePrecision] * a), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -2e19

   1. Initial program 98.2%

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

   3. Taylor expanded in a around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

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

      4. lower-*.f64 64.0

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

   5. Applied rewrites 64.0%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. associate-*l* N/A

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

      4. *-commutative N/A

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

      5. *-commutative N/A

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

      6. lower-*.f64 N/A

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

      7. lower-*.f64 63.9

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

   7. Applied rewrites 63.9%

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

   if -2e19 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 2.00000000000000001e41

   1. Initial program 91.7%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 52.4

         \[\leadsto 2 \cdot \color{blue}{x} \]

   5. Applied rewrites 52.4%

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

      1. lift-*.f64 N/A

         \[\leadsto 2 \cdot \color{blue}{x} \]

      2. count-2-rev N/A

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

      3. lower-+.f64 52.4

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

   7. Applied rewrites 52.4%

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

   if 2.00000000000000001e41 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 92.8%

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

   3. Taylor expanded in a around inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. *-commutative N/A

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

      4. lower-*.f64 59.2

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

   5. Applied rewrites 59.2%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. associate-*l* N/A

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

      4. *-commutative N/A

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

      5. *-commutative N/A

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

      6. *-commutative N/A

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

      7. associate-*r* N/A

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

      8. *-commutative N/A

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

      9. lower-*.f64 N/A

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

      10. *-commutative N/A

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

      11. lower-*.f64 59.2

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

   7. Applied rewrites 59.2%

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

Alternative 13: 64.5% accurate, 2.5× speedup

Math

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

FPCore

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 a) 27.0 (+ x x)))

C

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 * a), 27.0, (x + x));
}

Julia

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

Wolfram

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[(b * a), $MachinePrecision] * 27.0 + N[(x + x), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 93.5%

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

   1. +-commutative N/A

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

   2. *-commutative N/A

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

   3. lower-fma.f64 N/A

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

   4. *-commutative N/A

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

   5. lower-*.f64 N/A

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

   6. lower-*.f64 66.3

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

5. Applied rewrites 66.3%

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

   1. lift-*.f64 N/A

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

   2. count-2-rev N/A

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

   3. lower-+.f64 66.3

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

7. Applied rewrites 66.3%

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

Alternative 14: 31.1% accurate, 9.3× speedup

Math

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

FPCore

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

C

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.
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;
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])
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])
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])){:}
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.
code[x_, y_, z_, t_, a_, b_] := N[(x + x), $MachinePrecision]

Derivation

1. Initial program 93.5%

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

3. Taylor expanded in x around inf

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

   1. lower-*.f64 36.4

      \[\leadsto 2 \cdot \color{blue}{x} \]

5. Applied rewrites 36.4%

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

   1. lift-*.f64 N/A

      \[\leadsto 2 \cdot \color{blue}{x} \]

   2. count-2-rev N/A

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

   3. lower-+.f64 36.4

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

7. Applied rewrites 36.4%

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

Developer Target 1: 95.1% 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 2025043 
(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)))