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

Percentage Accurate: 95.4% → 98.6%

Time: 4.5s

Alternatives: 12

Speedup: 0.9×

• 27.1% 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: 95.4% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 98.6% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;t \leq 2 \cdot 10^{+148}:\\ \;\;\;\;\mathsf{fma}\left(\left(t \cdot z\right) \cdot -9, y, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(27 \cdot a, b, \mathsf{fma}\left(-9 \cdot t, z \cdot y, 2 \cdot x\right)\right)\\ \end{array} \end{array} \]

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 (<= t 2e+148)
   (fma (* (* t z) -9.0) y (fma (* b a) 27.0 (* 2.0 x)))
   (fma (* 27.0 a) b (fma (* -9.0 t) (* z y) (* 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 (t <= 2e+148) {
		tmp = fma(((t * z) * -9.0), y, fma((b * a), 27.0, (2.0 * x)));
	} else {
		tmp = fma((27.0 * a), b, fma((-9.0 * t), (z * y), (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 (t <= 2e+148)
		tmp = fma(Float64(Float64(t * z) * -9.0), y, fma(Float64(b * a), 27.0, Float64(2.0 * x)));
	else
		tmp = fma(Float64(27.0 * a), b, fma(Float64(-9.0 * t), Float64(z * y), 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[t, 2e+148], N[(N[(N[(t * z), $MachinePrecision] * -9.0), $MachinePrecision] * y + N[(N[(b * a), $MachinePrecision] * 27.0 + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(27.0 * a), $MachinePrecision] * b + N[(N[(-9.0 * t), $MachinePrecision] * N[(z * y), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < 2.0000000000000001e148

   1. Initial program 93.2%

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

      1. lift-+.f64 N/A

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

      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 94.9%

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

   if 2.0000000000000001e148 < t

   1. Initial program 97.0%

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

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

      4. lift-*.f64 N/A

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

      5. lift-*.f64 N/A

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

      6. lift-*.f64 N/A

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

      7. +-commutative N/A

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

      8. lift-*.f64 N/A

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

      9. lift-*.f64 N/A

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

      10. *-commutative N/A

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

      11. lower-fma.f64 N/A

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

      12. lower-*.f64 N/A

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

      13. *-commutative N/A

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

      14. *-commutative N/A

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

      15. associate-*r* N/A

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

      16. cancel-sign-sub-inv N/A

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

   4. Applied rewrites 99.9%

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

Alternative 2: 84.1% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -4 \cdot 10^{+196}:\\ \;\;\;\;\left(t \cdot z\right) \cdot \left(-9 \cdot y\right)\\ \mathbf{elif}\;t\_1 \leq 2 \cdot 10^{+54}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-9 \cdot t, z \cdot y, 2 \cdot x\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -4e+196)
     (* (* t z) (* -9.0 y))
     (if (<= t_1 2e+54)
       (fma (* b a) 27.0 (+ x x))
       (fma (* -9.0 t) (* z y) (* 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 t_1 = ((y * 9.0) * z) * t;
	double tmp;
	if (t_1 <= -4e+196) {
		tmp = (t * z) * (-9.0 * y);
	} else if (t_1 <= 2e+54) {
		tmp = fma((b * a), 27.0, (x + x));
	} else {
		tmp = fma((-9.0 * t), (z * y), (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)
	t_1 = Float64(Float64(Float64(y * 9.0) * z) * t)
	tmp = 0.0
	if (t_1 <= -4e+196)
		tmp = Float64(Float64(t * z) * Float64(-9.0 * y));
	elseif (t_1 <= 2e+54)
		tmp = fma(Float64(b * a), 27.0, Float64(x + x));
	else
		tmp = fma(Float64(-9.0 * t), Float64(z * y), 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_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -4e+196], N[(N[(t * z), $MachinePrecision] * N[(-9.0 * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+54], N[(N[(b * a), $MachinePrecision] * 27.0 + N[(x + x), $MachinePrecision]), $MachinePrecision], N[(N[(-9.0 * t), $MachinePrecision] * N[(z * y), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -3.9999999999999998e196

   1. Initial program 72.8%

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

   3. Taylor expanded in y around inf

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

      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 78.8

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

   5. Applied rewrites 78.8%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. *-commutative N/A

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

      4. associate-*l* N/A

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

      5. lift-*.f64 N/A

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

      6. associate-*r* N/A

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

      7. associate-*r* N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 91.6

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

   7. Applied rewrites 91.6%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. associate-*l* N/A

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

      5. lower-*.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 91.6

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

   9. Applied rewrites 91.6%

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

   if -3.9999999999999998e196 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 2.0000000000000002e54

   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 x around inf

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

      1. lower-*.f64 87.3

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

   5. Applied rewrites 87.3%

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

      1. lift-+.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. +-commutative N/A

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

      5. *-commutative N/A

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

      6. associate-*r* N/A

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

      7. *-commutative N/A

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

      8. lower-fma.f64 N/A

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

      9. *-commutative N/A

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

      10. lift-*.f64 87.9

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

      11. lift-*.f64 N/A

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

      12. *-commutative N/A

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

      13. lower-*.f64 87.9

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

   7. Applied rewrites 87.9%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 87.9

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

   9. Applied rewrites 87.9%

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

   if 2.0000000000000002e54 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 88.7%

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

   3. Taylor expanded in 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 86.6

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

   5. Applied rewrites 86.6%

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

Alternative 3: 81.9% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+184} \lor \neg \left(t\_1 \leq 5 \cdot 10^{+181}\right):\\ \;\;\;\;-9 \cdot \left(\left(y \cdot t\right) \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \end{array} \end{array} \]

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+184) (not (<= t_1 5e+181)))
     (* -9.0 (* (* y t) z))
     (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+184) || !(t_1 <= 5e+181)) {
		tmp = -9.0 * ((y * t) * z);
	} 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+184) || !(t_1 <= 5e+181))
		tmp = Float64(-9.0 * Float64(Float64(y * t) * z));
	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+184], N[Not[LessEqual[t$95$1, 5e+181]], $MachinePrecision]], N[(-9.0 * N[(N[(y * t), $MachinePrecision] * z), $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) < -4.9999999999999999e184 or 5.0000000000000003e181 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 78.8%

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

   3. Taylor expanded in y around inf

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

      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 77.7

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

   5. Applied rewrites 77.7%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. *-commutative N/A

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

      4. *-commutative N/A

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

      5. associate-*r* N/A

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

      6. lower-*.f64 N/A

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

      7. *-commutative N/A

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

      8. lower-*.f64 79.1

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

   7. Applied rewrites 79.1%

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

   if -4.9999999999999999e184 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 5.0000000000000003e181

   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 x around inf

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

      1. lower-*.f64 85.3

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

   5. Applied rewrites 85.3%

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

      1. lift-+.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. +-commutative N/A

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

      5. *-commutative N/A

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

      6. associate-*r* N/A

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

      7. *-commutative N/A

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

      8. lower-fma.f64 N/A

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

      9. *-commutative N/A

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

      10. lift-*.f64 85.9

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

      11. lift-*.f64 N/A

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

      12. *-commutative N/A

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

      13. lower-*.f64 85.9

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

   7. Applied rewrites 85.9%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 85.9

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

   9. Applied rewrites 85.9%

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

4. Final simplification 84.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq -5 \cdot 10^{+184} \lor \neg \left(\left(\left(y \cdot 9\right) \cdot z\right) \cdot t \leq 5 \cdot 10^{+181}\right):\\ \;\;\;\;-9 \cdot \left(\left(y \cdot t\right) \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 82.2% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\\ \mathbf{if}\;t\_1 \leq -4 \cdot 10^{+196}:\\ \;\;\;\;\left(t \cdot z\right) \cdot \left(-9 \cdot y\right)\\ \mathbf{elif}\;t\_1 \leq 5 \cdot 10^{+181}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot a, 27, x + x\right)\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(\left(y \cdot t\right) \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* (* y 9.0) z) t)))
   (if (<= t_1 -4e+196)
     (* (* t z) (* -9.0 y))
     (if (<= t_1 5e+181) (fma (* b a) 27.0 (+ x x)) (* -9.0 (* (* y t) z))))))

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 <= -4e+196) {
		tmp = (t * z) * (-9.0 * y);
	} else if (t_1 <= 5e+181) {
		tmp = fma((b * a), 27.0, (x + x));
	} else {
		tmp = -9.0 * ((y * t) * z);
	}
	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 <= -4e+196)
		tmp = Float64(Float64(t * z) * Float64(-9.0 * y));
	elseif (t_1 <= 5e+181)
		tmp = fma(Float64(b * a), 27.0, Float64(x + x));
	else
		tmp = Float64(-9.0 * Float64(Float64(y * t) * z));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]}, If[LessEqual[t$95$1, -4e+196], N[(N[(t * z), $MachinePrecision] * N[(-9.0 * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 5e+181], N[(N[(b * a), $MachinePrecision] * 27.0 + N[(x + x), $MachinePrecision]), $MachinePrecision], N[(-9.0 * N[(N[(y * t), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < -3.9999999999999998e196

   1. Initial program 72.8%

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

   3. Taylor expanded in y around inf

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

      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 78.8

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

   5. Applied rewrites 78.8%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. *-commutative N/A

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

      4. associate-*l* N/A

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

      5. lift-*.f64 N/A

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

      6. associate-*r* N/A

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

      7. associate-*r* N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 91.6

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

   7. Applied rewrites 91.6%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. associate-*l* N/A

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

      5. lower-*.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 91.6

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

   9. Applied rewrites 91.6%

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

   if -3.9999999999999998e196 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t) < 5.0000000000000003e181

   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 x around inf

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

      1. lower-*.f64 84.6

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

   5. Applied rewrites 84.6%

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

      1. lift-+.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. +-commutative N/A

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

      5. *-commutative N/A

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

      6. associate-*r* N/A

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

      7. *-commutative N/A

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

      8. lower-fma.f64 N/A

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

      9. *-commutative N/A

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

      10. lift-*.f64 85.2

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

      11. lift-*.f64 N/A

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

      12. *-commutative N/A

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

      13. lower-*.f64 85.2

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

   7. Applied rewrites 85.2%

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

      1. lift-*.f64 N/A

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

      2. *-commutative N/A

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

      3. count-2-rev N/A

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

      4. lift-+.f64 85.2

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

   9. Applied rewrites 85.2%

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

   if 5.0000000000000003e181 < (*.f64 (*.f64 (*.f64 y #s(literal 9 binary64)) z) t)

   1. Initial program 84.0%

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

   3. Taylor expanded in y around inf

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

      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 77.5

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

   5. Applied rewrites 77.5%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. *-commutative N/A

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

      4. *-commutative N/A

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

      5. associate-*r* N/A

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

      6. lower-*.f64 N/A

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

      7. *-commutative N/A

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

      8. lower-*.f64 71.1

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

   7. Applied rewrites 71.1%

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

Alternative 5: 97.4% accurate, 0.8× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;\left(y \cdot 9\right) \cdot z \leq 5 \cdot 10^{+301}:\\ \;\;\;\;\mathsf{fma}\left(27 \cdot a, b, \mathsf{fma}\left(-9 \cdot t, z \cdot y, 2 \cdot x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(t \cdot z\right) \cdot \left(-9 \cdot y\right)\\ \end{array} \end{array} \]

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 (<= (* (* y 9.0) z) 5e+301)
   (fma (* 27.0 a) b (fma (* -9.0 t) (* z y) (* 2.0 x)))
   (* (* t z) (* -9.0 y))))

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 (((y * 9.0) * z) <= 5e+301) {
		tmp = fma((27.0 * a), b, fma((-9.0 * t), (z * y), (2.0 * x)));
	} else {
		tmp = (t * z) * (-9.0 * y);
	}
	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 (Float64(Float64(y * 9.0) * z) <= 5e+301)
		tmp = fma(Float64(27.0 * a), b, fma(Float64(-9.0 * t), Float64(z * y), Float64(2.0 * x)));
	else
		tmp = Float64(Float64(t * z) * Float64(-9.0 * y));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision], 5e+301], N[(N[(27.0 * a), $MachinePrecision] * b + N[(N[(-9.0 * t), $MachinePrecision] * N[(z * y), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(t * z), $MachinePrecision] * N[(-9.0 * y), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 y #s(literal 9 binary64)) z) < 5.0000000000000004e301

   1. Initial program 96.5%

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

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

      4. lift-*.f64 N/A

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

      5. lift-*.f64 N/A

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

      6. lift-*.f64 N/A

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

      7. +-commutative N/A

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

      8. lift-*.f64 N/A

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

      9. lift-*.f64 N/A

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

      10. *-commutative N/A

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

      11. lower-fma.f64 N/A

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

      12. lower-*.f64 N/A

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

      13. *-commutative N/A

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

      14. *-commutative N/A

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

      15. associate-*r* N/A

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

      16. cancel-sign-sub-inv N/A

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

   4. Applied rewrites 98.2%

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

   if 5.0000000000000004e301 < (*.f64 (*.f64 y #s(literal 9 binary64)) z)

   1. Initial program 48.9%

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

   3. Taylor expanded in 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 55.5

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

   5. Applied rewrites 55.5%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. *-commutative N/A

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

      4. associate-*l* N/A

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

      5. lift-*.f64 N/A

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

      6. associate-*r* N/A

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

      7. associate-*r* N/A

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

      8. lower-*.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. *-commutative N/A

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

      12. lower-*.f64 87.0

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

   7. Applied rewrites 87.0%

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

      1. lift-*.f64 N/A

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

      2. lift-*.f64 N/A

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

      3. lift-*.f64 N/A

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

      4. associate-*l* N/A

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

      5. lower-*.f64 N/A

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

      6. *-commutative N/A

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

      7. lower-*.f64 N/A

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

      8. lower-*.f64 87.1

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

   9. Applied rewrites 87.1%

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

Alternative 6: 53.1% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+101} \lor \neg \left(t\_1 \leq 5 \cdot 10^{-10}\right):\\ \;\;\;\;\left(b \cdot a\right) \cdot 27\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \end{array} \]

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 -5e+101) (not (<= t_1 5e-10))) (* (* 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 = (a * 27.0) * b;
	double tmp;
	if ((t_1 <= -5e+101) || !(t_1 <= 5e-10)) {
		tmp = (b * a) * 27.0;
	} 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 <= (-5d+101)) .or. (.not. (t_1 <= 5d-10))) then
        tmp = (b * a) * 27.0d0
    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 <= -5e+101) || !(t_1 <= 5e-10)) {
		tmp = (b * a) * 27.0;
	} 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 <= -5e+101) or not (t_1 <= 5e-10):
		tmp = (b * a) * 27.0
	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 <= -5e+101) || !(t_1 <= 5e-10))
		tmp = Float64(Float64(b * a) * 27.0);
	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 <= -5e+101) || ~((t_1 <= 5e-10)))
		tmp = (b * a) * 27.0;
	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, -5e+101], N[Not[LessEqual[t$95$1, 5e-10]], $MachinePrecision]], N[(N[(b * a), $MachinePrecision] * 27.0), $MachinePrecision], N[(x + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -4.99999999999999989e101 or 5.00000000000000031e-10 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 91.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   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 66.4

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

   5. Applied rewrites 66.4%

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

   if -4.99999999999999989e101 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 5.00000000000000031e-10

   1. Initial program 95.5%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 46.9

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

   5. Applied rewrites 46.9%

      \[\leadsto \color{blue}{2 \cdot x} \]
   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 46.9

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

   7. Applied rewrites 46.9%

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

4. Final simplification 56.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(a \cdot 27\right) \cdot b \leq -5 \cdot 10^{+101} \lor \neg \left(\left(a \cdot 27\right) \cdot b \leq 5 \cdot 10^{-10}\right):\\ \;\;\;\;\left(b \cdot a\right) \cdot 27\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 53.1% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+101} \lor \neg \left(t\_1 \leq 5 \cdot 10^{-10}\right):\\ \;\;\;\;a \cdot \left(27 \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \end{array} \]

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 -5e+101) (not (<= t_1 5e-10))) (* a (* 27.0 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 <= -5e+101) || !(t_1 <= 5e-10)) {
		tmp = a * (27.0 * 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 <= (-5d+101)) .or. (.not. (t_1 <= 5d-10))) then
        tmp = a * (27.0d0 * 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 <= -5e+101) || !(t_1 <= 5e-10)) {
		tmp = a * (27.0 * 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 <= -5e+101) or not (t_1 <= 5e-10):
		tmp = a * (27.0 * 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 <= -5e+101) || !(t_1 <= 5e-10))
		tmp = Float64(a * Float64(27.0 * 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 <= -5e+101) || ~((t_1 <= 5e-10)))
		tmp = a * (27.0 * 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, -5e+101], N[Not[LessEqual[t$95$1, 5e-10]], $MachinePrecision]], N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision], N[(x + x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -4.99999999999999989e101 or 5.00000000000000031e-10 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 91.8%

      \[\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \]
   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 66.4

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

   5. Applied rewrites 66.4%

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

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

      5. associate-*l* N/A

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

      6. lower-*.f64 N/A

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

      7. lower-*.f64 66.4

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

   7. Applied rewrites 66.4%

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

   if -4.99999999999999989e101 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 5.00000000000000031e-10

   1. Initial program 95.5%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 46.9

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

   5. Applied rewrites 46.9%

      \[\leadsto \color{blue}{2 \cdot x} \]
   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 46.9

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

   7. Applied rewrites 46.9%

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

4. Final simplification 56.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(a \cdot 27\right) \cdot b \leq -5 \cdot 10^{+101} \lor \neg \left(\left(a \cdot 27\right) \cdot b \leq 5 \cdot 10^{-10}\right):\\ \;\;\;\;a \cdot \left(27 \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;x + x\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 53.1% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(a \cdot 27\right) \cdot b\\ \mathbf{if}\;t\_1 \leq -5 \cdot 10^{+101}:\\ \;\;\;\;\left(27 \cdot a\right) \cdot b\\ \mathbf{elif}\;t\_1 \leq 5 \cdot 10^{-10}:\\ \;\;\;\;x + x\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(27 \cdot b\right)\\ \end{array} \end{array} \]

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 (* (* a 27.0) b)))
   (if (<= t_1 -5e+101)
     (* (* 27.0 a) b)
     (if (<= t_1 5e-10) (+ x x) (* a (* 27.0 b))))))

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 <= -5e+101) {
		tmp = (27.0 * a) * b;
	} else if (t_1 <= 5e-10) {
		tmp = x + x;
	} else {
		tmp = a * (27.0 * b);
	}
	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 <= (-5d+101)) then
        tmp = (27.0d0 * a) * b
    else if (t_1 <= 5d-10) then
        tmp = x + x
    else
        tmp = a * (27.0d0 * b)
    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 <= -5e+101) {
		tmp = (27.0 * a) * b;
	} else if (t_1 <= 5e-10) {
		tmp = x + x;
	} else {
		tmp = a * (27.0 * b);
	}
	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 <= -5e+101:
		tmp = (27.0 * a) * b
	elif t_1 <= 5e-10:
		tmp = x + x
	else:
		tmp = a * (27.0 * b)
	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 <= -5e+101)
		tmp = Float64(Float64(27.0 * a) * b);
	elseif (t_1 <= 5e-10)
		tmp = Float64(x + x);
	else
		tmp = Float64(a * Float64(27.0 * b));
	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 <= -5e+101)
		tmp = (27.0 * a) * b;
	elseif (t_1 <= 5e-10)
		tmp = x + x;
	else
		tmp = a * (27.0 * b);
	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, -5e+101], N[(N[(27.0 * a), $MachinePrecision] * b), $MachinePrecision], If[LessEqual[t$95$1, 5e-10], N[(x + x), $MachinePrecision], N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 a #s(literal 27 binary64)) b) < -4.99999999999999989e101

   1. Initial program 89.0%

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

   3. Taylor expanded in 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 67.8

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

   5. Applied rewrites 67.8%

      \[\leadsto \color{blue}{\left(b \cdot a\right) \cdot 27} \]
   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. lift-*.f64 67.7

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

   7. Applied rewrites 67.7%

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

   if -4.99999999999999989e101 < (*.f64 (*.f64 a #s(literal 27 binary64)) b) < 5.00000000000000031e-10

   1. Initial program 95.5%

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

   3. Taylor expanded in x around inf

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

      1. lower-*.f64 46.9

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

   5. Applied rewrites 46.9%

      \[\leadsto \color{blue}{2 \cdot x} \]
   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 46.9

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

   7. Applied rewrites 46.9%

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

   if 5.00000000000000031e-10 < (*.f64 (*.f64 a #s(literal 27 binary64)) b)

   1. Initial program 93.4%

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

   3. Taylor expanded in 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 65.6

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

   5. Applied rewrites 65.6%

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

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

      5. associate-*l* N/A

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

      6. lower-*.f64 N/A

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

      7. lower-*.f64 65.7

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

   7. Applied rewrites 65.7%

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

Alternative 9: 98.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;t \leq 8 \cdot 10^{-48}:\\ \;\;\;\;\mathsf{fma}\left(\left(t \cdot y\right) \cdot -9, z, \mathsf{fma}\left(b \cdot a, 27, 2 \cdot x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(27 \cdot a, b, \mathsf{fma}\left(-9 \cdot t, z \cdot y, 2 \cdot x\right)\right)\\ \end{array} \end{array} \]

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 (<= t 8e-48)
   (fma (* (* t y) -9.0) z (fma (* b a) 27.0 (* 2.0 x)))
   (fma (* 27.0 a) b (fma (* -9.0 t) (* z y) (* 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 (t <= 8e-48) {
		tmp = fma(((t * y) * -9.0), z, fma((b * a), 27.0, (2.0 * x)));
	} else {
		tmp = fma((27.0 * a), b, fma((-9.0 * t), (z * y), (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 (t <= 8e-48)
		tmp = fma(Float64(Float64(t * y) * -9.0), z, fma(Float64(b * a), 27.0, Float64(2.0 * x)));
	else
		tmp = fma(Float64(27.0 * a), b, fma(Float64(-9.0 * t), Float64(z * y), 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[t, 8e-48], N[(N[(N[(t * y), $MachinePrecision] * -9.0), $MachinePrecision] * z + N[(N[(b * a), $MachinePrecision] * 27.0 + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(27.0 * a), $MachinePrecision] * b + N[(N[(-9.0 * t), $MachinePrecision] * N[(z * y), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < 7.9999999999999998e-48

   1. Initial program 92.1%

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

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

      8. lift-*.f64 N/A

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

      9. *-commutative N/A

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

      10. associate-*r* N/A

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

      11. distribute-lft-neg-in N/A

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

      12. metadata-eval N/A

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

      13. associate-*r* N/A

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

      14. *-commutative N/A

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

      15. lift-*.f64 N/A

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

      16. lift-*.f64 N/A

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

      17. *-commutative N/A

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

      18. associate-*r* N/A

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

   4. Applied rewrites 93.2%

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

   if 7.9999999999999998e-48 < t

   1. Initial program 97.3%

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

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

      4. lift-*.f64 N/A

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

      5. lift-*.f64 N/A

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

      6. lift-*.f64 N/A

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

      7. +-commutative N/A

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

      8. lift-*.f64 N/A

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

      9. lift-*.f64 N/A

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

      10. *-commutative N/A

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

      11. lower-fma.f64 N/A

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

      12. lower-*.f64 N/A

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

      13. *-commutative N/A

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

      14. *-commutative N/A

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

      15. associate-*r* N/A

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

      16. cancel-sign-sub-inv N/A

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

   4. Applied rewrites 98.6%

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

Alternative 10: 64.2% 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 93.7%

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

3. Taylor expanded in x around inf

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

   1. lower-*.f64 67.6

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

5. Applied rewrites 67.6%

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

   1. lift-+.f64 N/A

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

   2. lift-*.f64 N/A

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

   3. lift-*.f64 N/A

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

   4. +-commutative N/A

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

   5. *-commutative N/A

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

   6. associate-*r* N/A

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

   7. *-commutative N/A

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

   8. lower-fma.f64 N/A

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

   9. *-commutative N/A

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

   10. lift-*.f64 68.1

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

   11. lift-*.f64 N/A

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

   12. *-commutative N/A

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

   13. lower-*.f64 68.1

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

7. Applied rewrites 68.1%

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

   1. lift-*.f64 N/A

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

   2. *-commutative N/A

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

   3. count-2-rev N/A

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

   4. lift-+.f64 68.1

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

9. Applied rewrites 68.1%

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

Alternative 11: 64.2% accurate, 2.5× speedup

Math

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

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 a (* b 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(a, (b * 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(a, Float64(b * 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[(a * N[(b * 27.0), $MachinePrecision] + N[(x + x), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 93.7%

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

3. Taylor expanded in x around inf

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

   1. lower-*.f64 67.6

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

5. Applied rewrites 67.6%

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

   1. lift-+.f64 N/A

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

   2. lift-*.f64 N/A

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

   3. lift-*.f64 N/A

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

   4. +-commutative N/A

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

   5. associate-*l* N/A

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

   6. lower-fma.f64 N/A

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

   7. *-commutative N/A

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

   8. lower-*.f64 68.1

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

   9. lift-*.f64 N/A

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

   10. *-commutative N/A

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

   11. lower-*.f64 68.1

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

7. Applied rewrites 68.1%

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

   1. lift-*.f64 N/A

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

   2. *-commutative N/A

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

   3. count-2-rev N/A

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

   4. lift-+.f64 68.1

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

9. Applied rewrites 68.1%

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

Alternative 12: 30.5% 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 93.7%

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

3. Taylor expanded in x around inf

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

   1. lower-*.f64 30.7

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

5. Applied rewrites 30.7%

   \[\leadsto \color{blue}{2 \cdot x} \]
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 30.7

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

7. Applied rewrites 30.7%

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

Developer Target 1: 95.0% 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 2025076 
(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)))