Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 28.8% → 52.1%

Time: 18.8s

Alternatives: 32

Speedup: 5.8×

• 89.4% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (+
  (-
   (+
    (+
     (-
      (* (- (* x y) (* z t)) (- (* a b) (* c i)))
      (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
     (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
    (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
   (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
  (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 28.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (+
  (-
   (+
    (+
     (-
      (* (- (* x y) (* z t)) (- (* a b) (* c i)))
      (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
     (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
    (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
   (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
  (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 52.1% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot b - c \cdot i\\ t_2 := \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot t\_1 - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right)\\ \mathbf{if}\;t\_2 \leq \infty:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(\mathsf{fma}\left(-1, z \cdot t\_1, j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a b) (* c i)))
        (t_2
         (+
          (-
           (+
            (+
             (-
              (* (- (* x y) (* z t)) t_1)
              (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
             (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
            (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
           (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
          (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))))
   (if (<= t_2 INFINITY)
     t_2
     (*
      t
      (-
       (fma -1.0 (* z t_1) (* j (- (* b y4) (* i y5))))
       (* y2 (- (* c y4) (* a y5))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * b) - (c * i);
	double t_2 = (((((((x * y) - (z * t)) * t_1) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
	double tmp;
	if (t_2 <= ((double) INFINITY)) {
		tmp = t_2;
	} else {
		tmp = t * (fma(-1.0, (z * t_1), (j * ((b * y4) - (i * y5)))) - (y2 * ((c * y4) - (a * y5))));
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(a * b) - Float64(c * i))
	t_2 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * t_1) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
	tmp = 0.0
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = Float64(t * Float64(fma(-1.0, Float64(z * t_1), Float64(j * Float64(Float64(b * y4) - Float64(i * y5)))) - Float64(y2 * Float64(Float64(c * y4) - Float64(a * y5)))));
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, Infinity], t$95$2, N[(t * N[(N[(-1.0 * N[(z * t$95$1), $MachinePrecision] + N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y2 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0)))) < +inf.0

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   if +inf.0 < (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0))))

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 2: 43.9% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y - t \cdot z\\ t_2 := j \cdot x - k \cdot z\\ t_3 := a \cdot b - c \cdot i\\ t_4 := x \cdot \left(\mathsf{fma}\left(y, t\_3, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_5 := j \cdot t - k \cdot y\\ \mathbf{if}\;x \leq -1.05 \cdot 10^{+203}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;x \leq -3.6 \cdot 10^{+45}:\\ \;\;\;\;b \cdot \left(\mathsf{fma}\left(a, t\_1, y4 \cdot t\_5\right) - y0 \cdot t\_2\right)\\ \mathbf{elif}\;x \leq -8 \cdot 10^{-28}:\\ \;\;\;\;-1 \cdot \left(i \cdot \left(\mathsf{fma}\left(c, t\_1, y5 \cdot t\_5\right) - y1 \cdot t\_2\right)\right)\\ \mathbf{elif}\;x \leq -2.5 \cdot 10^{-302}:\\ \;\;\;\;y \cdot \left(\mathsf{fma}\left(-1, k \cdot \left(b \cdot y4 - i \cdot y5\right), x \cdot t\_3\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)\\ \mathbf{elif}\;x \leq 3.6 \cdot 10^{-19}:\\ \;\;\;\;c \cdot \left(\mathsf{fma}\left(-1, i \cdot t\_1, y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y) (* t z)))
        (t_2 (- (* j x) (* k z)))
        (t_3 (- (* a b) (* c i)))
        (t_4
         (*
          x
          (-
           (fma y t_3 (* y2 (- (* c y0) (* a y1))))
           (* j (- (* b y0) (* i y1))))))
        (t_5 (- (* j t) (* k y))))
   (if (<= x -1.05e+203)
     t_4
     (if (<= x -3.6e+45)
       (* b (- (fma a t_1 (* y4 t_5)) (* y0 t_2)))
       (if (<= x -8e-28)
         (* -1.0 (* i (- (fma c t_1 (* y5 t_5)) (* y1 t_2))))
         (if (<= x -2.5e-302)
           (*
            y
            (-
             (fma -1.0 (* k (- (* b y4) (* i y5))) (* x t_3))
             (* -1.0 (* y3 (- (* c y4) (* a y5))))))
           (if (<= x 3.6e-19)
             (*
              c
              (-
               (fma -1.0 (* i t_1) (* y0 (- (* x y2) (* y3 z))))
               (* y4 (- (* t y2) (* y y3)))))
             t_4)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (x * y) - (t * z);
	double t_2 = (j * x) - (k * z);
	double t_3 = (a * b) - (c * i);
	double t_4 = x * (fma(y, t_3, (y2 * ((c * y0) - (a * y1)))) - (j * ((b * y0) - (i * y1))));
	double t_5 = (j * t) - (k * y);
	double tmp;
	if (x <= -1.05e+203) {
		tmp = t_4;
	} else if (x <= -3.6e+45) {
		tmp = b * (fma(a, t_1, (y4 * t_5)) - (y0 * t_2));
	} else if (x <= -8e-28) {
		tmp = -1.0 * (i * (fma(c, t_1, (y5 * t_5)) - (y1 * t_2)));
	} else if (x <= -2.5e-302) {
		tmp = y * (fma(-1.0, (k * ((b * y4) - (i * y5))), (x * t_3)) - (-1.0 * (y3 * ((c * y4) - (a * y5)))));
	} else if (x <= 3.6e-19) {
		tmp = c * (fma(-1.0, (i * t_1), (y0 * ((x * y2) - (y3 * z)))) - (y4 * ((t * y2) - (y * y3))));
	} else {
		tmp = t_4;
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(x * y) - Float64(t * z))
	t_2 = Float64(Float64(j * x) - Float64(k * z))
	t_3 = Float64(Float64(a * b) - Float64(c * i))
	t_4 = Float64(x * Float64(fma(y, t_3, Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) - Float64(j * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_5 = Float64(Float64(j * t) - Float64(k * y))
	tmp = 0.0
	if (x <= -1.05e+203)
		tmp = t_4;
	elseif (x <= -3.6e+45)
		tmp = Float64(b * Float64(fma(a, t_1, Float64(y4 * t_5)) - Float64(y0 * t_2)));
	elseif (x <= -8e-28)
		tmp = Float64(-1.0 * Float64(i * Float64(fma(c, t_1, Float64(y5 * t_5)) - Float64(y1 * t_2))));
	elseif (x <= -2.5e-302)
		tmp = Float64(y * Float64(fma(-1.0, Float64(k * Float64(Float64(b * y4) - Float64(i * y5))), Float64(x * t_3)) - Float64(-1.0 * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))));
	elseif (x <= 3.6e-19)
		tmp = Float64(c * Float64(fma(-1.0, Float64(i * t_1), Float64(y0 * Float64(Float64(x * y2) - Float64(y3 * z)))) - Float64(y4 * Float64(Float64(t * y2) - Float64(y * y3)))));
	else
		tmp = t_4;
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(x * N[(N[(y * t$95$3 + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(j * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.05e+203], t$95$4, If[LessEqual[x, -3.6e+45], N[(b * N[(N[(a * t$95$1 + N[(y4 * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(y0 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -8e-28], N[(-1.0 * N[(i * N[(N[(c * t$95$1 + N[(y5 * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(y1 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2.5e-302], N[(y * N[(N[(-1.0 * N[(k * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$3), $MachinePrecision]), $MachinePrecision] - N[(-1.0 * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.6e-19], N[(c * N[(N[(-1.0 * N[(i * t$95$1), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$4]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -1.04999999999999992e203 or 3.6000000000000001e-19 < x

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.04999999999999992e203 < x < -3.6e45

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -3.6e45 < x < -7.99999999999999977e-28

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in i around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(i \cdot \color{blue}{\left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y1 \cdot \left(j \cdot x - k \cdot z\right)}\right)\right) \]

   4. Applied rewrites 37.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\mathsf{fma}\left(c, x \cdot y - t \cdot z, y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   if -7.99999999999999977e-28 < x < -2.50000000000000017e-302

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y around inf

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \color{blue}{\left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - \color{blue}{-1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)}\right) \]

   4. Applied rewrites 35.8%

      \[\leadsto \color{blue}{y \cdot \left(\mathsf{fma}\left(-1, k \cdot \left(b \cdot y4 - i \cdot y5\right), x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if -2.50000000000000017e-302 < x < 3.6000000000000001e-19

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - \color{blue}{y4 \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{c \cdot \left(\mathsf{fma}\left(-1, i \cdot \left(x \cdot y - t \cdot z\right), y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 3: 43.5% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot x - k \cdot z\\ t_2 := c \cdot y0 - a \cdot y1\\ t_3 := x \cdot y - t \cdot z\\ t_4 := a \cdot b - c \cdot i\\ t_5 := b \cdot y0 - i \cdot y1\\ t_6 := x \cdot \left(\mathsf{fma}\left(y, t\_4, y2 \cdot t\_2\right) - j \cdot t\_5\right)\\ t_7 := j \cdot t - k \cdot y\\ \mathbf{if}\;x \leq -1.05 \cdot 10^{+203}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;x \leq -3.6 \cdot 10^{+45}:\\ \;\;\;\;b \cdot \left(\mathsf{fma}\left(a, t\_3, y4 \cdot t\_7\right) - y0 \cdot t\_1\right)\\ \mathbf{elif}\;x \leq -3 \cdot 10^{-27}:\\ \;\;\;\;-1 \cdot \left(i \cdot \left(\mathsf{fma}\left(c, t\_3, y5 \cdot t\_7\right) - y1 \cdot t\_1\right)\right)\\ \mathbf{elif}\;x \leq -3.8 \cdot 10^{-236}:\\ \;\;\;\;-1 \cdot \left(z \cdot \left(\mathsf{fma}\left(t, t\_4, y3 \cdot t\_2\right) - k \cdot t\_5\right)\right)\\ \mathbf{elif}\;x \leq 3.6 \cdot 10^{-19}:\\ \;\;\;\;c \cdot \left(\mathsf{fma}\left(-1, i \cdot t\_3, y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_6\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* j x) (* k z)))
        (t_2 (- (* c y0) (* a y1)))
        (t_3 (- (* x y) (* t z)))
        (t_4 (- (* a b) (* c i)))
        (t_5 (- (* b y0) (* i y1)))
        (t_6 (* x (- (fma y t_4 (* y2 t_2)) (* j t_5))))
        (t_7 (- (* j t) (* k y))))
   (if (<= x -1.05e+203)
     t_6
     (if (<= x -3.6e+45)
       (* b (- (fma a t_3 (* y4 t_7)) (* y0 t_1)))
       (if (<= x -3e-27)
         (* -1.0 (* i (- (fma c t_3 (* y5 t_7)) (* y1 t_1))))
         (if (<= x -3.8e-236)
           (* -1.0 (* z (- (fma t t_4 (* y3 t_2)) (* k t_5))))
           (if (<= x 3.6e-19)
             (*
              c
              (-
               (fma -1.0 (* i t_3) (* y0 (- (* x y2) (* y3 z))))
               (* y4 (- (* t y2) (* y y3)))))
             t_6)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * x) - (k * z);
	double t_2 = (c * y0) - (a * y1);
	double t_3 = (x * y) - (t * z);
	double t_4 = (a * b) - (c * i);
	double t_5 = (b * y0) - (i * y1);
	double t_6 = x * (fma(y, t_4, (y2 * t_2)) - (j * t_5));
	double t_7 = (j * t) - (k * y);
	double tmp;
	if (x <= -1.05e+203) {
		tmp = t_6;
	} else if (x <= -3.6e+45) {
		tmp = b * (fma(a, t_3, (y4 * t_7)) - (y0 * t_1));
	} else if (x <= -3e-27) {
		tmp = -1.0 * (i * (fma(c, t_3, (y5 * t_7)) - (y1 * t_1)));
	} else if (x <= -3.8e-236) {
		tmp = -1.0 * (z * (fma(t, t_4, (y3 * t_2)) - (k * t_5)));
	} else if (x <= 3.6e-19) {
		tmp = c * (fma(-1.0, (i * t_3), (y0 * ((x * y2) - (y3 * z)))) - (y4 * ((t * y2) - (y * y3))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(j * x) - Float64(k * z))
	t_2 = Float64(Float64(c * y0) - Float64(a * y1))
	t_3 = Float64(Float64(x * y) - Float64(t * z))
	t_4 = Float64(Float64(a * b) - Float64(c * i))
	t_5 = Float64(Float64(b * y0) - Float64(i * y1))
	t_6 = Float64(x * Float64(fma(y, t_4, Float64(y2 * t_2)) - Float64(j * t_5)))
	t_7 = Float64(Float64(j * t) - Float64(k * y))
	tmp = 0.0
	if (x <= -1.05e+203)
		tmp = t_6;
	elseif (x <= -3.6e+45)
		tmp = Float64(b * Float64(fma(a, t_3, Float64(y4 * t_7)) - Float64(y0 * t_1)));
	elseif (x <= -3e-27)
		tmp = Float64(-1.0 * Float64(i * Float64(fma(c, t_3, Float64(y5 * t_7)) - Float64(y1 * t_1))));
	elseif (x <= -3.8e-236)
		tmp = Float64(-1.0 * Float64(z * Float64(fma(t, t_4, Float64(y3 * t_2)) - Float64(k * t_5))));
	elseif (x <= 3.6e-19)
		tmp = Float64(c * Float64(fma(-1.0, Float64(i * t_3), Float64(y0 * Float64(Float64(x * y2) - Float64(y3 * z)))) - Float64(y4 * Float64(Float64(t * y2) - Float64(y * y3)))));
	else
		tmp = t_6;
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(x * N[(N[(y * t$95$4 + N[(y2 * t$95$2), $MachinePrecision]), $MachinePrecision] - N[(j * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.05e+203], t$95$6, If[LessEqual[x, -3.6e+45], N[(b * N[(N[(a * t$95$3 + N[(y4 * t$95$7), $MachinePrecision]), $MachinePrecision] - N[(y0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3e-27], N[(-1.0 * N[(i * N[(N[(c * t$95$3 + N[(y5 * t$95$7), $MachinePrecision]), $MachinePrecision] - N[(y1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3.8e-236], N[(-1.0 * N[(z * N[(N[(t * t$95$4 + N[(y3 * t$95$2), $MachinePrecision]), $MachinePrecision] - N[(k * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.6e-19], N[(c * N[(N[(-1.0 * N[(i * t$95$3), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$6]]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -1.04999999999999992e203 or 3.6000000000000001e-19 < x

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.04999999999999992e203 < x < -3.6e45

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -3.6e45 < x < -3.0000000000000001e-27

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in i around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(i \cdot \color{blue}{\left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y1 \cdot \left(j \cdot x - k \cdot z\right)}\right)\right) \]

   4. Applied rewrites 37.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\mathsf{fma}\left(c, x \cdot y - t \cdot z, y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   if -3.0000000000000001e-27 < x < -3.7999999999999999e-236

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in z around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(z \cdot \color{blue}{\left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{k \cdot \left(b \cdot y0 - i \cdot y1\right)}\right)\right) \]

   4. Applied rewrites 36.6%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\mathsf{fma}\left(t, a \cdot b - c \cdot i, y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if -3.7999999999999999e-236 < x < 3.6000000000000001e-19

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - \color{blue}{y4 \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{c \cdot \left(\mathsf{fma}\left(-1, i \cdot \left(x \cdot y - t \cdot z\right), y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 4: 41.8% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y - t \cdot z\\ t_2 := x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_3 := j \cdot t - k \cdot y\\ t_4 := j \cdot x - k \cdot z\\ \mathbf{if}\;x \leq -1.05 \cdot 10^{+203}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq -3.6 \cdot 10^{+45}:\\ \;\;\;\;b \cdot \left(\mathsf{fma}\left(a, t\_1, y4 \cdot t\_3\right) - y0 \cdot t\_4\right)\\ \mathbf{elif}\;x \leq -1.45 \cdot 10^{-128}:\\ \;\;\;\;-1 \cdot \left(i \cdot \left(\mathsf{fma}\left(c, t\_1, y5 \cdot t\_3\right) - y1 \cdot t\_4\right)\right)\\ \mathbf{elif}\;x \leq 42000:\\ \;\;\;\;y4 \cdot \left(\mathsf{fma}\left(b, t\_3, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y) (* t z)))
        (t_2
         (*
          x
          (-
           (fma y (- (* a b) (* c i)) (* y2 (- (* c y0) (* a y1))))
           (* j (- (* b y0) (* i y1))))))
        (t_3 (- (* j t) (* k y)))
        (t_4 (- (* j x) (* k z))))
   (if (<= x -1.05e+203)
     t_2
     (if (<= x -3.6e+45)
       (* b (- (fma a t_1 (* y4 t_3)) (* y0 t_4)))
       (if (<= x -1.45e-128)
         (* -1.0 (* i (- (fma c t_1 (* y5 t_3)) (* y1 t_4))))
         (if (<= x 42000.0)
           (*
            y4
            (-
             (fma b t_3 (* y1 (- (* k y2) (* j y3))))
             (* c (- (* t y2) (* y y3)))))
           t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (x * y) - (t * z);
	double t_2 = x * (fma(y, ((a * b) - (c * i)), (y2 * ((c * y0) - (a * y1)))) - (j * ((b * y0) - (i * y1))));
	double t_3 = (j * t) - (k * y);
	double t_4 = (j * x) - (k * z);
	double tmp;
	if (x <= -1.05e+203) {
		tmp = t_2;
	} else if (x <= -3.6e+45) {
		tmp = b * (fma(a, t_1, (y4 * t_3)) - (y0 * t_4));
	} else if (x <= -1.45e-128) {
		tmp = -1.0 * (i * (fma(c, t_1, (y5 * t_3)) - (y1 * t_4)));
	} else if (x <= 42000.0) {
		tmp = y4 * (fma(b, t_3, (y1 * ((k * y2) - (j * y3)))) - (c * ((t * y2) - (y * y3))));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(x * y) - Float64(t * z))
	t_2 = Float64(x * Float64(fma(y, Float64(Float64(a * b) - Float64(c * i)), Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) - Float64(j * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_3 = Float64(Float64(j * t) - Float64(k * y))
	t_4 = Float64(Float64(j * x) - Float64(k * z))
	tmp = 0.0
	if (x <= -1.05e+203)
		tmp = t_2;
	elseif (x <= -3.6e+45)
		tmp = Float64(b * Float64(fma(a, t_1, Float64(y4 * t_3)) - Float64(y0 * t_4)));
	elseif (x <= -1.45e-128)
		tmp = Float64(-1.0 * Float64(i * Float64(fma(c, t_1, Float64(y5 * t_3)) - Float64(y1 * t_4))));
	elseif (x <= 42000.0)
		tmp = Float64(y4 * Float64(fma(b, t_3, Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) - Float64(c * Float64(Float64(t * y2) - Float64(y * y3)))));
	else
		tmp = t_2;
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(j * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.05e+203], t$95$2, If[LessEqual[x, -3.6e+45], N[(b * N[(N[(a * t$95$1 + N[(y4 * t$95$3), $MachinePrecision]), $MachinePrecision] - N[(y0 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.45e-128], N[(-1.0 * N[(i * N[(N[(c * t$95$1 + N[(y5 * t$95$3), $MachinePrecision]), $MachinePrecision] - N[(y1 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 42000.0], N[(y4 * N[(N[(b * t$95$3 + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if x < -1.04999999999999992e203 or 42000 < x

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.04999999999999992e203 < x < -3.6e45

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -3.6e45 < x < -1.45e-128

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in i around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(i \cdot \color{blue}{\left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y1 \cdot \left(j \cdot x - k \cdot z\right)}\right)\right) \]

   4. Applied rewrites 37.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\mathsf{fma}\left(c, x \cdot y - t \cdot z, y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   if -1.45e-128 < x < 42000

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 5: 40.8% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;x \leq -1.05 \cdot 10^{+203}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -4.8 \cdot 10^{-241}:\\ \;\;\;\;b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)\\ \mathbf{elif}\;x \leq 1.9 \cdot 10^{-165}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq 3.1 \cdot 10^{-20}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          x
          (-
           (fma y (- (* a b) (* c i)) (* y2 (- (* c y0) (* a y1))))
           (* j (- (* b y0) (* i y1)))))))
   (if (<= x -1.05e+203)
     t_1
     (if (<= x -4.8e-241)
       (*
        b
        (-
         (fma a (- (* x y) (* t z)) (* y4 (- (* j t) (* k y))))
         (* y0 (- (* j x) (* k z)))))
       (if (<= x 1.9e-165)
         (* y4 (* c (- (* y y3) (* t y2))))
         (if (<= x 3.1e-20) (* y3 (* y5 (- (* j y0) (* a y)))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (fma(y, ((a * b) - (c * i)), (y2 * ((c * y0) - (a * y1)))) - (j * ((b * y0) - (i * y1))));
	double tmp;
	if (x <= -1.05e+203) {
		tmp = t_1;
	} else if (x <= -4.8e-241) {
		tmp = b * (fma(a, ((x * y) - (t * z)), (y4 * ((j * t) - (k * y)))) - (y0 * ((j * x) - (k * z))));
	} else if (x <= 1.9e-165) {
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	} else if (x <= 3.1e-20) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(x * Float64(fma(y, Float64(Float64(a * b) - Float64(c * i)), Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) - Float64(j * Float64(Float64(b * y0) - Float64(i * y1)))))
	tmp = 0.0
	if (x <= -1.05e+203)
		tmp = t_1;
	elseif (x <= -4.8e-241)
		tmp = Float64(b * Float64(fma(a, Float64(Float64(x * y) - Float64(t * z)), Float64(y4 * Float64(Float64(j * t) - Float64(k * y)))) - Float64(y0 * Float64(Float64(j * x) - Float64(k * z)))));
	elseif (x <= 1.9e-165)
		tmp = Float64(y4 * Float64(c * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (x <= 3.1e-20)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	else
		tmp = t_1;
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(j * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.05e+203], t$95$1, If[LessEqual[x, -4.8e-241], N[(b * N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.9e-165], N[(y4 * N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.1e-20], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if x < -1.04999999999999992e203 or 3.1e-20 < x

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.04999999999999992e203 < x < -4.8e-241

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -4.8e-241 < x < 1.90000000000000009e-165

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      4. lower-*.f64 27.3

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.3%

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

   if 1.90000000000000009e-165 < x < 3.1e-20

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 6: 38.7% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_2 := j \cdot t - k \cdot y\\ \mathbf{if}\;x \leq -1.05 \cdot 10^{+203}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -1.7 \cdot 10^{-238}:\\ \;\;\;\;b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot t\_2\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)\\ \mathbf{elif}\;x \leq 42000:\\ \;\;\;\;y4 \cdot \left(\mathsf{fma}\left(b, t\_2, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          x
          (-
           (fma y (- (* a b) (* c i)) (* y2 (- (* c y0) (* a y1))))
           (* j (- (* b y0) (* i y1))))))
        (t_2 (- (* j t) (* k y))))
   (if (<= x -1.05e+203)
     t_1
     (if (<= x -1.7e-238)
       (*
        b
        (- (fma a (- (* x y) (* t z)) (* y4 t_2)) (* y0 (- (* j x) (* k z)))))
       (if (<= x 42000.0)
         (*
          y4
          (-
           (fma b t_2 (* y1 (- (* k y2) (* j y3))))
           (* c (- (* t y2) (* y y3)))))
         t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (fma(y, ((a * b) - (c * i)), (y2 * ((c * y0) - (a * y1)))) - (j * ((b * y0) - (i * y1))));
	double t_2 = (j * t) - (k * y);
	double tmp;
	if (x <= -1.05e+203) {
		tmp = t_1;
	} else if (x <= -1.7e-238) {
		tmp = b * (fma(a, ((x * y) - (t * z)), (y4 * t_2)) - (y0 * ((j * x) - (k * z))));
	} else if (x <= 42000.0) {
		tmp = y4 * (fma(b, t_2, (y1 * ((k * y2) - (j * y3)))) - (c * ((t * y2) - (y * y3))));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(x * Float64(fma(y, Float64(Float64(a * b) - Float64(c * i)), Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) - Float64(j * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_2 = Float64(Float64(j * t) - Float64(k * y))
	tmp = 0.0
	if (x <= -1.05e+203)
		tmp = t_1;
	elseif (x <= -1.7e-238)
		tmp = Float64(b * Float64(fma(a, Float64(Float64(x * y) - Float64(t * z)), Float64(y4 * t_2)) - Float64(y0 * Float64(Float64(j * x) - Float64(k * z)))));
	elseif (x <= 42000.0)
		tmp = Float64(y4 * Float64(fma(b, t_2, Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) - Float64(c * Float64(Float64(t * y2) - Float64(y * y3)))));
	else
		tmp = t_1;
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(j * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.05e+203], t$95$1, If[LessEqual[x, -1.7e-238], N[(b * N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 42000.0], N[(y4 * N[(N[(b * t$95$2 + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 3 regimes

2. if x < -1.04999999999999992e203 or 42000 < x

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.04999999999999992e203 < x < -1.69999999999999992e-238

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -1.69999999999999992e-238 < x < 42000

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 7: 38.3% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -2.35 \cdot 10^{+176}:\\ \;\;\;\;a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -7.8 \cdot 10^{+114}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.25 \cdot 10^{-23}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)\\ \mathbf{elif}\;y3 \leq -1.35 \cdot 10^{-212}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right)\\ \mathbf{elif}\;y3 \leq 4.5 \cdot 10^{-171}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right)\\ \mathbf{elif}\;y3 \leq 1.26 \cdot 10^{+79}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y3 \leq 1.85 \cdot 10^{+235}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(y3 \cdot \mathsf{fma}\left(-1, j \cdot y4, a \cdot z\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -2.35e+176)
   (* a (* y (- (* b x) (* y3 y5))))
   (if (<= y3 -7.8e+114)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= y3 -1.25e-23)
       (* b (* y0 (- (* k z) (* j x))))
       (if (<= y3 -1.35e-212)
         (* y4 (* y2 (- (* k y1) (* c t))))
         (if (<= y3 4.5e-171)
           (* b (* a (- (* x y) (* t z))))
           (if (<= y3 1.26e+79)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y3 1.85e+235)
               (* a (* y3 (- (* y1 z) (* y y5))))
               (* y1 (* y3 (fma -1.0 (* j y4) (* a z))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.35e+176) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -7.8e+114) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y3 <= -1.25e-23) {
		tmp = b * (y0 * ((k * z) - (j * x)));
	} else if (y3 <= -1.35e-212) {
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y3 <= 1.85e+235) {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	} else {
		tmp = y1 * (y3 * fma(-1.0, (j * y4), (a * z)));
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y3 <= -2.35e+176)
		tmp = Float64(a * Float64(y * Float64(Float64(b * x) - Float64(y3 * y5))));
	elseif (y3 <= -7.8e+114)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y3 <= -1.25e-23)
		tmp = Float64(b * Float64(y0 * Float64(Float64(k * z) - Float64(j * x))));
	elseif (y3 <= -1.35e-212)
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(c * t))));
	elseif (y3 <= 4.5e-171)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(t * z))));
	elseif (y3 <= 1.26e+79)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y3 <= 1.85e+235)
		tmp = Float64(a * Float64(y3 * Float64(Float64(y1 * z) - Float64(y * y5))));
	else
		tmp = Float64(y1 * Float64(y3 * fma(-1.0, Float64(j * y4), Float64(a * z))));
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y3, -2.35e+176], N[(a * N[(y * N[(N[(b * x), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -7.8e+114], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.25e-23], N[(b * N[(y0 * N[(N[(k * z), $MachinePrecision] - N[(j * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.35e-212], N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(c * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 4.5e-171], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.26e+79], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.85e+235], N[(a * N[(y3 * N[(N[(y1 * z), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(y3 * N[(-1.0 * N[(j * y4), $MachinePrecision] + N[(a * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y3 < -2.34999999999999991e176

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - \color{blue}{y3 \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

      4. lower-*.f64 26.9

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

   7. Applied rewrites 26.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   if -2.34999999999999991e176 < y3 < -7.8000000000000001e114

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4 - i \cdot y5\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - \color{blue}{i \cdot y5}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot \color{blue}{y5}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

      5. lower-*.f64 27.6

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   7. Applied rewrites 27.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -7.8000000000000001e114 < y3 < -1.2500000000000001e-23

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in y0 around inf

      \[\leadsto b \cdot \left(y0 \cdot \color{blue}{\left(k \cdot z - j \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - \color{blue}{j \cdot x}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot \color{blue}{x}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right) \]

      4. lower-*.f64 26.1

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right) \]

   7. Applied rewrites 26.1%

      \[\leadsto b \cdot \left(y0 \cdot \color{blue}{\left(k \cdot z - j \cdot x\right)}\right) \]

   if -1.2500000000000001e-23 < y3 < -1.34999999999999991e-212

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto y4 \cdot \left(y2 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - \color{blue}{c \cdot t}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot \color{blue}{t}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

      4. lower-*.f64 26.1

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

   7. Applied rewrites 26.1%

      \[\leadsto y4 \cdot \left(y2 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]

   if -1.34999999999999991e-212 < y3 < 4.5000000000000004e-171

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in a around inf

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

      1. lower-*.f64 N/A

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

      2. lower--.f64 N/A

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

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

      4. lower-*.f64 26.4

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

   7. Applied rewrites 26.4%

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

   if 4.5000000000000004e-171 < y3 < 1.26e79

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.26e79 < y3 < 1.8499999999999999e235

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   if 1.8499999999999999e235 < y3

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y3 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y3 \cdot \color{blue}{\left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{y \cdot \left(c \cdot y4 - a \cdot y5\right)}\right)\right) \]

   4. Applied rewrites 36.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\mathsf{fma}\left(j, y1 \cdot y4 - y0 \cdot y5, z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   5. Taylor expanded in y1 around -inf

      \[\leadsto y1 \cdot \color{blue}{\left(y3 \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y3 \cdot \color{blue}{\left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y3 \cdot \left(-1 \cdot \left(j \cdot y4\right) + \color{blue}{a \cdot z}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto y1 \cdot \left(y3 \cdot \mathsf{fma}\left(-1, j \cdot \color{blue}{y4}, a \cdot z\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y3 \cdot \mathsf{fma}\left(-1, j \cdot y4, a \cdot z\right)\right) \]

      5. lower-*.f64 27.0

         \[\leadsto y1 \cdot \left(y3 \cdot \mathsf{fma}\left(-1, j \cdot y4, a \cdot z\right)\right) \]

   7. Applied rewrites 27.0%

      \[\leadsto y1 \cdot \color{blue}{\left(y3 \cdot \mathsf{fma}\left(-1, j \cdot y4, a \cdot z\right)\right)} \]
3. Recombined 8 regimes into one program.
4. Add Preprocessing

Alternative 8: 36.4% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y5 \leq -50000000000:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{elif}\;y5 \leq -7.6 \cdot 10^{-138}:\\ \;\;\;\;t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y5 \leq 2.5 \cdot 10^{+142}:\\ \;\;\;\;b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y5 -50000000000.0)
   (* y3 (* y5 (- (* j y0) (* a y))))
   (if (<= y5 -7.6e-138)
     (* t (* c (- (* i z) (* y2 y4))))
     (if (<= y5 2.5e+142)
       (*
        b
        (-
         (fma a (- (* x y) (* t z)) (* y4 (- (* j t) (* k y))))
         (* y0 (- (* j x) (* k z)))))
       (* k (* y5 (fma -1.0 (* y0 y2) (* i y))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -50000000000.0) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y5 <= -7.6e-138) {
		tmp = t * (c * ((i * z) - (y2 * y4)));
	} else if (y5 <= 2.5e+142) {
		tmp = b * (fma(a, ((x * y) - (t * z)), (y4 * ((j * t) - (k * y)))) - (y0 * ((j * x) - (k * z))));
	} else {
		tmp = k * (y5 * fma(-1.0, (y0 * y2), (i * y)));
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y5 <= -50000000000.0)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	elseif (y5 <= -7.6e-138)
		tmp = Float64(t * Float64(c * Float64(Float64(i * z) - Float64(y2 * y4))));
	elseif (y5 <= 2.5e+142)
		tmp = Float64(b * Float64(fma(a, Float64(Float64(x * y) - Float64(t * z)), Float64(y4 * Float64(Float64(j * t) - Float64(k * y)))) - Float64(y0 * Float64(Float64(j * x) - Float64(k * z)))));
	else
		tmp = Float64(k * Float64(y5 * fma(-1.0, Float64(y0 * y2), Float64(i * y))));
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y5, -50000000000.0], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -7.6e-138], N[(t * N[(c * N[(N[(i * z), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.5e+142], N[(b * N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(y5 * N[(-1.0 * N[(y0 * y2), $MachinePrecision] + N[(i * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y5 < -5e10

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if -5e10 < y5 < -7.6000000000000005e-138

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto t \cdot \left(c \cdot \color{blue}{\left(i \cdot z - y2 \cdot y4\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - \color{blue}{y2 \cdot y4}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot \color{blue}{y4}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right) \]

      4. lower-*.f64 27.0

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right) \]

   7. Applied rewrites 27.0%

      \[\leadsto t \cdot \left(c \cdot \color{blue}{\left(i \cdot z - y2 \cdot y4\right)}\right) \]

   if -7.6000000000000005e-138 < y5 < 2.5000000000000001e142

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 2.5000000000000001e142 < y5

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 9: 32.8% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -2.35 \cdot 10^{+176}:\\ \;\;\;\;a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -7.8 \cdot 10^{+114}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.25 \cdot 10^{-23}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)\\ \mathbf{elif}\;y3 \leq -1.35 \cdot 10^{-212}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right)\\ \mathbf{elif}\;y3 \leq 4.5 \cdot 10^{-171}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right)\\ \mathbf{elif}\;y3 \leq 1.26 \cdot 10^{+79}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -2.35e+176)
   (* a (* y (- (* b x) (* y3 y5))))
   (if (<= y3 -7.8e+114)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= y3 -1.25e-23)
       (* b (* y0 (- (* k z) (* j x))))
       (if (<= y3 -1.35e-212)
         (* y4 (* y2 (- (* k y1) (* c t))))
         (if (<= y3 4.5e-171)
           (* b (* a (- (* x y) (* t z))))
           (if (<= y3 1.26e+79)
             (* x (* y2 (- (* c y0) (* a y1))))
             (* a (* y3 (- (* y1 z) (* y y5)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.35e+176) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -7.8e+114) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y3 <= -1.25e-23) {
		tmp = b * (y0 * ((k * z) - (j * x)));
	} else if (y3 <= -1.35e-212) {
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y3 <= (-2.35d+176)) then
        tmp = a * (y * ((b * x) - (y3 * y5)))
    else if (y3 <= (-7.8d+114)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y3 <= (-1.25d-23)) then
        tmp = b * (y0 * ((k * z) - (j * x)))
    else if (y3 <= (-1.35d-212)) then
        tmp = y4 * (y2 * ((k * y1) - (c * t)))
    else if (y3 <= 4.5d-171) then
        tmp = b * (a * ((x * y) - (t * z)))
    else if (y3 <= 1.26d+79) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else
        tmp = a * (y3 * ((y1 * z) - (y * y5)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.35e+176) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -7.8e+114) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y3 <= -1.25e-23) {
		tmp = b * (y0 * ((k * z) - (j * x)));
	} else if (y3 <= -1.35e-212) {
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y3 <= -2.35e+176:
		tmp = a * (y * ((b * x) - (y3 * y5)))
	elif y3 <= -7.8e+114:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y3 <= -1.25e-23:
		tmp = b * (y0 * ((k * z) - (j * x)))
	elif y3 <= -1.35e-212:
		tmp = y4 * (y2 * ((k * y1) - (c * t)))
	elif y3 <= 4.5e-171:
		tmp = b * (a * ((x * y) - (t * z)))
	elif y3 <= 1.26e+79:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	else:
		tmp = a * (y3 * ((y1 * z) - (y * y5)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y3 <= -2.35e+176)
		tmp = Float64(a * Float64(y * Float64(Float64(b * x) - Float64(y3 * y5))));
	elseif (y3 <= -7.8e+114)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y3 <= -1.25e-23)
		tmp = Float64(b * Float64(y0 * Float64(Float64(k * z) - Float64(j * x))));
	elseif (y3 <= -1.35e-212)
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(c * t))));
	elseif (y3 <= 4.5e-171)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(t * z))));
	elseif (y3 <= 1.26e+79)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	else
		tmp = Float64(a * Float64(y3 * Float64(Float64(y1 * z) - Float64(y * y5))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y3 <= -2.35e+176)
		tmp = a * (y * ((b * x) - (y3 * y5)));
	elseif (y3 <= -7.8e+114)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y3 <= -1.25e-23)
		tmp = b * (y0 * ((k * z) - (j * x)));
	elseif (y3 <= -1.35e-212)
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	elseif (y3 <= 4.5e-171)
		tmp = b * (a * ((x * y) - (t * z)));
	elseif (y3 <= 1.26e+79)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	else
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y3, -2.35e+176], N[(a * N[(y * N[(N[(b * x), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -7.8e+114], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.25e-23], N[(b * N[(y0 * N[(N[(k * z), $MachinePrecision] - N[(j * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.35e-212], N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(c * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 4.5e-171], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.26e+79], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(y3 * N[(N[(y1 * z), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y3 < -2.34999999999999991e176

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - \color{blue}{y3 \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

      4. lower-*.f64 26.9

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

   7. Applied rewrites 26.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   if -2.34999999999999991e176 < y3 < -7.8000000000000001e114

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4 - i \cdot y5\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - \color{blue}{i \cdot y5}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot \color{blue}{y5}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

      5. lower-*.f64 27.6

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   7. Applied rewrites 27.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -7.8000000000000001e114 < y3 < -1.2500000000000001e-23

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in y0 around inf

      \[\leadsto b \cdot \left(y0 \cdot \color{blue}{\left(k \cdot z - j \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - \color{blue}{j \cdot x}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot \color{blue}{x}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right) \]

      4. lower-*.f64 26.1

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right) \]

   7. Applied rewrites 26.1%

      \[\leadsto b \cdot \left(y0 \cdot \color{blue}{\left(k \cdot z - j \cdot x\right)}\right) \]

   if -1.2500000000000001e-23 < y3 < -1.34999999999999991e-212

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto y4 \cdot \left(y2 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - \color{blue}{c \cdot t}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot \color{blue}{t}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

      4. lower-*.f64 26.1

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

   7. Applied rewrites 26.1%

      \[\leadsto y4 \cdot \left(y2 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]

   if -1.34999999999999991e-212 < y3 < 4.5000000000000004e-171

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in a around inf

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

      1. lower-*.f64 N/A

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

      2. lower--.f64 N/A

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

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

      4. lower-*.f64 26.4

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

   7. Applied rewrites 26.4%

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

   if 4.5000000000000004e-171 < y3 < 1.26e79

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.26e79 < y3

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
3. Recombined 7 regimes into one program.
4. Add Preprocessing

Alternative 10: 32.3% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y1 \leq -1.78 \cdot 10^{+109}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq -2.5 \cdot 10^{-235}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq -6.5 \cdot 10^{-291}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{elif}\;y1 \leq 1.85 \cdot 10^{-96}:\\ \;\;\;\;y4 \cdot \left(-1 \cdot \left(b \cdot \left(k \cdot y\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y1 \leq 102000000:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y1 -1.78e+109)
   (* x (* j (- (* i y1) (* b y0))))
   (if (<= y1 -2.5e-235)
     (* b (* j (- (* t y4) (* x y0))))
     (if (<= y1 -6.5e-291)
       (* y3 (* y5 (- (* j y0) (* a y))))
       (if (<= y1 1.85e-96)
         (* y4 (- (* -1.0 (* b (* k y))) (* c (- (* t y2) (* y y3)))))
         (if (<= y1 102000000.0)
           (* x (* y2 (- (* c y0) (* a y1))))
           (* y4 (* y2 (- (* k y1) (* c t))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y1 <= -1.78e+109) {
		tmp = x * (j * ((i * y1) - (b * y0)));
	} else if (y1 <= -2.5e-235) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else if (y1 <= -6.5e-291) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y1 <= 1.85e-96) {
		tmp = y4 * ((-1.0 * (b * (k * y))) - (c * ((t * y2) - (y * y3))));
	} else if (y1 <= 102000000.0) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y1 <= (-1.78d+109)) then
        tmp = x * (j * ((i * y1) - (b * y0)))
    else if (y1 <= (-2.5d-235)) then
        tmp = b * (j * ((t * y4) - (x * y0)))
    else if (y1 <= (-6.5d-291)) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else if (y1 <= 1.85d-96) then
        tmp = y4 * (((-1.0d0) * (b * (k * y))) - (c * ((t * y2) - (y * y3))))
    else if (y1 <= 102000000.0d0) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else
        tmp = y4 * (y2 * ((k * y1) - (c * t)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y1 <= -1.78e+109) {
		tmp = x * (j * ((i * y1) - (b * y0)));
	} else if (y1 <= -2.5e-235) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else if (y1 <= -6.5e-291) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y1 <= 1.85e-96) {
		tmp = y4 * ((-1.0 * (b * (k * y))) - (c * ((t * y2) - (y * y3))));
	} else if (y1 <= 102000000.0) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y1 <= -1.78e+109:
		tmp = x * (j * ((i * y1) - (b * y0)))
	elif y1 <= -2.5e-235:
		tmp = b * (j * ((t * y4) - (x * y0)))
	elif y1 <= -6.5e-291:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	elif y1 <= 1.85e-96:
		tmp = y4 * ((-1.0 * (b * (k * y))) - (c * ((t * y2) - (y * y3))))
	elif y1 <= 102000000.0:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	else:
		tmp = y4 * (y2 * ((k * y1) - (c * t)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y1 <= -1.78e+109)
		tmp = Float64(x * Float64(j * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y1 <= -2.5e-235)
		tmp = Float64(b * Float64(j * Float64(Float64(t * y4) - Float64(x * y0))));
	elseif (y1 <= -6.5e-291)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	elseif (y1 <= 1.85e-96)
		tmp = Float64(y4 * Float64(Float64(-1.0 * Float64(b * Float64(k * y))) - Float64(c * Float64(Float64(t * y2) - Float64(y * y3)))));
	elseif (y1 <= 102000000.0)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	else
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(c * t))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y1 <= -1.78e+109)
		tmp = x * (j * ((i * y1) - (b * y0)));
	elseif (y1 <= -2.5e-235)
		tmp = b * (j * ((t * y4) - (x * y0)));
	elseif (y1 <= -6.5e-291)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	elseif (y1 <= 1.85e-96)
		tmp = y4 * ((-1.0 * (b * (k * y))) - (c * ((t * y2) - (y * y3))));
	elseif (y1 <= 102000000.0)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	else
		tmp = y4 * (y2 * ((k * y1) - (c * t)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y1, -1.78e+109], N[(x * N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -2.5e-235], N[(b * N[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -6.5e-291], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.85e-96], N[(y4 * N[(N[(-1.0 * N[(b * N[(k * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 102000000.0], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(c * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if y1 < -1.7800000000000001e109

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto x \cdot \left(j \cdot \color{blue}{\left(i \cdot y1 - b \cdot y0\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(j \cdot \left(i \cdot y1 - \color{blue}{b \cdot y0}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot \color{blue}{y0}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right) \]

      4. lower-*.f64 26.5

         \[\leadsto x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto x \cdot \left(j \cdot \color{blue}{\left(i \cdot y1 - b \cdot y0\right)}\right) \]

   if -1.7800000000000001e109 < y1 < -2.4999999999999999e-235

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto b \cdot \left(j \cdot \color{blue}{\left(t \cdot y4 - x \cdot y0\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(j \cdot \left(t \cdot y4 - \color{blue}{x \cdot y0}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot \color{blue}{y0}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right) \]

      4. lower-*.f64 26.7

         \[\leadsto b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto b \cdot \left(j \cdot \color{blue}{\left(t \cdot y4 - x \cdot y0\right)}\right) \]

   if -2.4999999999999999e-235 < y1 < -6.50000000000000002e-291

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if -6.50000000000000002e-291 < y1 < 1.84999999999999993e-96

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto y4 \cdot \left(-1 \cdot \left(b \cdot \left(k \cdot y\right)\right) - \color{blue}{c} \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(-1 \cdot \left(b \cdot \left(k \cdot y\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(-1 \cdot \left(b \cdot \left(k \cdot y\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      3. lower-*.f64 32.0

         \[\leadsto y4 \cdot \left(-1 \cdot \left(b \cdot \left(k \cdot y\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

   7. Applied rewrites 32.0%

      \[\leadsto y4 \cdot \left(-1 \cdot \left(b \cdot \left(k \cdot y\right)\right) - \color{blue}{c} \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

   if 1.84999999999999993e-96 < y1 < 1.02e8

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.02e8 < y1

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto y4 \cdot \left(y2 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - \color{blue}{c \cdot t}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot \color{blue}{t}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

      4. lower-*.f64 26.1

         \[\leadsto y4 \cdot \left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

   7. Applied rewrites 26.1%

      \[\leadsto y4 \cdot \left(y2 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]
3. Recombined 6 regimes into one program.
4. Add Preprocessing

Alternative 11: 31.7% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -2.35 \cdot 10^{+176}:\\ \;\;\;\;a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -7.8 \cdot 10^{+114}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.2 \cdot 10^{-23}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)\\ \mathbf{elif}\;y3 \leq -1.35 \cdot 10^{-212}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right)\\ \mathbf{elif}\;y3 \leq 4.5 \cdot 10^{-171}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right)\\ \mathbf{elif}\;y3 \leq 1.26 \cdot 10^{+79}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -2.35e+176)
   (* a (* y (- (* b x) (* y3 y5))))
   (if (<= y3 -7.8e+114)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= y3 -1.2e-23)
       (* b (* y0 (- (* k z) (* j x))))
       (if (<= y3 -1.35e-212)
         (* y2 (* y4 (- (* k y1) (* c t))))
         (if (<= y3 4.5e-171)
           (* b (* a (- (* x y) (* t z))))
           (if (<= y3 1.26e+79)
             (* x (* y2 (- (* c y0) (* a y1))))
             (* a (* y3 (- (* y1 z) (* y y5)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.35e+176) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -7.8e+114) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y3 <= -1.2e-23) {
		tmp = b * (y0 * ((k * z) - (j * x)));
	} else if (y3 <= -1.35e-212) {
		tmp = y2 * (y4 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y3 <= (-2.35d+176)) then
        tmp = a * (y * ((b * x) - (y3 * y5)))
    else if (y3 <= (-7.8d+114)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y3 <= (-1.2d-23)) then
        tmp = b * (y0 * ((k * z) - (j * x)))
    else if (y3 <= (-1.35d-212)) then
        tmp = y2 * (y4 * ((k * y1) - (c * t)))
    else if (y3 <= 4.5d-171) then
        tmp = b * (a * ((x * y) - (t * z)))
    else if (y3 <= 1.26d+79) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else
        tmp = a * (y3 * ((y1 * z) - (y * y5)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.35e+176) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -7.8e+114) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y3 <= -1.2e-23) {
		tmp = b * (y0 * ((k * z) - (j * x)));
	} else if (y3 <= -1.35e-212) {
		tmp = y2 * (y4 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y3 <= -2.35e+176:
		tmp = a * (y * ((b * x) - (y3 * y5)))
	elif y3 <= -7.8e+114:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y3 <= -1.2e-23:
		tmp = b * (y0 * ((k * z) - (j * x)))
	elif y3 <= -1.35e-212:
		tmp = y2 * (y4 * ((k * y1) - (c * t)))
	elif y3 <= 4.5e-171:
		tmp = b * (a * ((x * y) - (t * z)))
	elif y3 <= 1.26e+79:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	else:
		tmp = a * (y3 * ((y1 * z) - (y * y5)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y3 <= -2.35e+176)
		tmp = Float64(a * Float64(y * Float64(Float64(b * x) - Float64(y3 * y5))));
	elseif (y3 <= -7.8e+114)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y3 <= -1.2e-23)
		tmp = Float64(b * Float64(y0 * Float64(Float64(k * z) - Float64(j * x))));
	elseif (y3 <= -1.35e-212)
		tmp = Float64(y2 * Float64(y4 * Float64(Float64(k * y1) - Float64(c * t))));
	elseif (y3 <= 4.5e-171)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(t * z))));
	elseif (y3 <= 1.26e+79)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	else
		tmp = Float64(a * Float64(y3 * Float64(Float64(y1 * z) - Float64(y * y5))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y3 <= -2.35e+176)
		tmp = a * (y * ((b * x) - (y3 * y5)));
	elseif (y3 <= -7.8e+114)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y3 <= -1.2e-23)
		tmp = b * (y0 * ((k * z) - (j * x)));
	elseif (y3 <= -1.35e-212)
		tmp = y2 * (y4 * ((k * y1) - (c * t)));
	elseif (y3 <= 4.5e-171)
		tmp = b * (a * ((x * y) - (t * z)));
	elseif (y3 <= 1.26e+79)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	else
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y3, -2.35e+176], N[(a * N[(y * N[(N[(b * x), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -7.8e+114], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.2e-23], N[(b * N[(y0 * N[(N[(k * z), $MachinePrecision] - N[(j * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.35e-212], N[(y2 * N[(y4 * N[(N[(k * y1), $MachinePrecision] - N[(c * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 4.5e-171], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.26e+79], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(y3 * N[(N[(y1 * z), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y3 < -2.34999999999999991e176

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - \color{blue}{y3 \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

      4. lower-*.f64 26.9

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

   7. Applied rewrites 26.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   if -2.34999999999999991e176 < y3 < -7.8000000000000001e114

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4 - i \cdot y5\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - \color{blue}{i \cdot y5}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot \color{blue}{y5}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

      5. lower-*.f64 27.6

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   7. Applied rewrites 27.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -7.8000000000000001e114 < y3 < -1.19999999999999998e-23

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in y0 around inf

      \[\leadsto b \cdot \left(y0 \cdot \color{blue}{\left(k \cdot z - j \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - \color{blue}{j \cdot x}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot \color{blue}{x}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right) \]

      4. lower-*.f64 26.1

         \[\leadsto b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right) \]

   7. Applied rewrites 26.1%

      \[\leadsto b \cdot \left(y0 \cdot \color{blue}{\left(k \cdot z - j \cdot x\right)}\right) \]

   if -1.19999999999999998e-23 < y3 < -1.34999999999999991e-212

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto y2 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - \color{blue}{c \cdot t}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot \color{blue}{t}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

      5. lower-*.f64 26.6

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto y2 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right)} \]

   if -1.34999999999999991e-212 < y3 < 4.5000000000000004e-171

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in a around inf

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

      1. lower-*.f64 N/A

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

      2. lower--.f64 N/A

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

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

      4. lower-*.f64 26.4

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

   7. Applied rewrites 26.4%

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

   if 4.5000000000000004e-171 < y3 < 1.26e79

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.26e79 < y3

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
3. Recombined 7 regimes into one program.
4. Add Preprocessing

Alternative 12: 31.4% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y5 \leq -50000000000:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{elif}\;y5 \leq -1.25 \cdot 10^{-141}:\\ \;\;\;\;t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y5 \leq -5.6 \cdot 10^{-195}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right)\\ \mathbf{elif}\;y5 \leq 2.7 \cdot 10^{+94}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;-1 \cdot \left(y2 \cdot \left(y5 \cdot \left(k \cdot y0 - a \cdot t\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y5 -50000000000.0)
   (* y3 (* y5 (- (* j y0) (* a y))))
   (if (<= y5 -1.25e-141)
     (* t (* c (- (* i z) (* y2 y4))))
     (if (<= y5 -5.6e-195)
       (* b (* a (- (* x y) (* t z))))
       (if (<= y5 2.7e+94)
         (* b (- (* y4 (- (* j t) (* k y))) (* y0 (- (* j x) (* k z)))))
         (* -1.0 (* y2 (* y5 (- (* k y0) (* a t))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -50000000000.0) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y5 <= -1.25e-141) {
		tmp = t * (c * ((i * z) - (y2 * y4)));
	} else if (y5 <= -5.6e-195) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y5 <= 2.7e+94) {
		tmp = b * ((y4 * ((j * t) - (k * y))) - (y0 * ((j * x) - (k * z))));
	} else {
		tmp = -1.0 * (y2 * (y5 * ((k * y0) - (a * t))));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y5 <= (-50000000000.0d0)) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else if (y5 <= (-1.25d-141)) then
        tmp = t * (c * ((i * z) - (y2 * y4)))
    else if (y5 <= (-5.6d-195)) then
        tmp = b * (a * ((x * y) - (t * z)))
    else if (y5 <= 2.7d+94) then
        tmp = b * ((y4 * ((j * t) - (k * y))) - (y0 * ((j * x) - (k * z))))
    else
        tmp = (-1.0d0) * (y2 * (y5 * ((k * y0) - (a * t))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -50000000000.0) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y5 <= -1.25e-141) {
		tmp = t * (c * ((i * z) - (y2 * y4)));
	} else if (y5 <= -5.6e-195) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y5 <= 2.7e+94) {
		tmp = b * ((y4 * ((j * t) - (k * y))) - (y0 * ((j * x) - (k * z))));
	} else {
		tmp = -1.0 * (y2 * (y5 * ((k * y0) - (a * t))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y5 <= -50000000000.0:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	elif y5 <= -1.25e-141:
		tmp = t * (c * ((i * z) - (y2 * y4)))
	elif y5 <= -5.6e-195:
		tmp = b * (a * ((x * y) - (t * z)))
	elif y5 <= 2.7e+94:
		tmp = b * ((y4 * ((j * t) - (k * y))) - (y0 * ((j * x) - (k * z))))
	else:
		tmp = -1.0 * (y2 * (y5 * ((k * y0) - (a * t))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y5 <= -50000000000.0)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	elseif (y5 <= -1.25e-141)
		tmp = Float64(t * Float64(c * Float64(Float64(i * z) - Float64(y2 * y4))));
	elseif (y5 <= -5.6e-195)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(t * z))));
	elseif (y5 <= 2.7e+94)
		tmp = Float64(b * Float64(Float64(y4 * Float64(Float64(j * t) - Float64(k * y))) - Float64(y0 * Float64(Float64(j * x) - Float64(k * z)))));
	else
		tmp = Float64(-1.0 * Float64(y2 * Float64(y5 * Float64(Float64(k * y0) - Float64(a * t)))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y5 <= -50000000000.0)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	elseif (y5 <= -1.25e-141)
		tmp = t * (c * ((i * z) - (y2 * y4)));
	elseif (y5 <= -5.6e-195)
		tmp = b * (a * ((x * y) - (t * z)));
	elseif (y5 <= 2.7e+94)
		tmp = b * ((y4 * ((j * t) - (k * y))) - (y0 * ((j * x) - (k * z))));
	else
		tmp = -1.0 * (y2 * (y5 * ((k * y0) - (a * t))));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y5, -50000000000.0], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1.25e-141], N[(t * N[(c * N[(N[(i * z), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -5.6e-195], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.7e+94], N[(b * N[(N[(y4 * N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(-1.0 * N[(y2 * N[(y5 * N[(N[(k * y0), $MachinePrecision] - N[(a * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y5 < -5e10

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if -5e10 < y5 < -1.25e-141

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto t \cdot \left(c \cdot \color{blue}{\left(i \cdot z - y2 \cdot y4\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - \color{blue}{y2 \cdot y4}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot \color{blue}{y4}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right) \]

      4. lower-*.f64 27.0

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right) \]

   7. Applied rewrites 27.0%

      \[\leadsto t \cdot \left(c \cdot \color{blue}{\left(i \cdot z - y2 \cdot y4\right)}\right) \]

   if -1.25e-141 < y5 < -5.60000000000000007e-195

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in a around inf

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

      1. lower-*.f64 N/A

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

      2. lower--.f64 N/A

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

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

      4. lower-*.f64 26.4

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

   7. Applied rewrites 26.4%

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

   if -5.60000000000000007e-195 < y5 < 2.7000000000000001e94

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in a around 0

      \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - \color{blue}{y0} \cdot \left(j \cdot x - k \cdot z\right)\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. lower-*.f64 34.0

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

   7. Applied rewrites 34.0%

      \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - \color{blue}{y0} \cdot \left(j \cdot x - k \cdot z\right)\right) \]

   if 2.7000000000000001e94 < y5

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto -1 \cdot \left(y2 \cdot \color{blue}{\left(y5 \cdot \left(k \cdot y0 - a \cdot t\right)\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y2 \cdot \left(y5 \cdot \color{blue}{\left(k \cdot y0 - a \cdot t\right)}\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y2 \cdot \left(y5 \cdot \left(k \cdot y0 - \color{blue}{a \cdot t}\right)\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y2 \cdot \left(y5 \cdot \left(k \cdot y0 - a \cdot \color{blue}{t}\right)\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y2 \cdot \left(y5 \cdot \left(k \cdot y0 - a \cdot t\right)\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto -1 \cdot \left(y2 \cdot \left(y5 \cdot \left(k \cdot y0 - a \cdot t\right)\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto -1 \cdot \left(y2 \cdot \color{blue}{\left(y5 \cdot \left(k \cdot y0 - a \cdot t\right)\right)}\right) \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 13: 31.3% accurate, 3.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right)\\ \mathbf{if}\;c \leq -2.4 \cdot 10^{+149}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq -1.05 \cdot 10^{-15}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -3.5 \cdot 10^{-233}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{elif}\;c \leq 7 \cdot 10^{-297}:\\ \;\;\;\;a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq 2.8 \cdot 10^{-37}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* t (* c (- (* i z) (* y2 y4))))))
   (if (<= c -2.4e+149)
     t_1
     (if (<= c -1.05e-15)
       (* x (* y2 (- (* c y0) (* a y1))))
       (if (<= c -3.5e-233)
         (* y3 (* y5 (- (* j y0) (* a y))))
         (if (<= c 7e-297)
           (* a (* y (- (* b x) (* y3 y5))))
           (if (<= c 2.8e-37) (* y1 (* y4 (- (* k y2) (* j y3)))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = t * (c * ((i * z) - (y2 * y4)));
	double tmp;
	if (c <= -2.4e+149) {
		tmp = t_1;
	} else if (c <= -1.05e-15) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (c <= -3.5e-233) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (c <= 7e-297) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (c <= 2.8e-37) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else {
		tmp = t_1;
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = t * (c * ((i * z) - (y2 * y4)))
    if (c <= (-2.4d+149)) then
        tmp = t_1
    else if (c <= (-1.05d-15)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (c <= (-3.5d-233)) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else if (c <= 7d-297) then
        tmp = a * (y * ((b * x) - (y3 * y5)))
    else if (c <= 2.8d-37) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = t * (c * ((i * z) - (y2 * y4)));
	double tmp;
	if (c <= -2.4e+149) {
		tmp = t_1;
	} else if (c <= -1.05e-15) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (c <= -3.5e-233) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (c <= 7e-297) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (c <= 2.8e-37) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = t * (c * ((i * z) - (y2 * y4)))
	tmp = 0
	if c <= -2.4e+149:
		tmp = t_1
	elif c <= -1.05e-15:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif c <= -3.5e-233:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	elif c <= 7e-297:
		tmp = a * (y * ((b * x) - (y3 * y5)))
	elif c <= 2.8e-37:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(t * Float64(c * Float64(Float64(i * z) - Float64(y2 * y4))))
	tmp = 0.0
	if (c <= -2.4e+149)
		tmp = t_1;
	elseif (c <= -1.05e-15)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (c <= -3.5e-233)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	elseif (c <= 7e-297)
		tmp = Float64(a * Float64(y * Float64(Float64(b * x) - Float64(y3 * y5))));
	elseif (c <= 2.8e-37)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = t * (c * ((i * z) - (y2 * y4)));
	tmp = 0.0;
	if (c <= -2.4e+149)
		tmp = t_1;
	elseif (c <= -1.05e-15)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (c <= -3.5e-233)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	elseif (c <= 7e-297)
		tmp = a * (y * ((b * x) - (y3 * y5)));
	elseif (c <= 2.8e-37)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(t * N[(c * N[(N[(i * z), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -2.4e+149], t$95$1, If[LessEqual[c, -1.05e-15], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -3.5e-233], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 7e-297], N[(a * N[(y * N[(N[(b * x), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.8e-37], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if c < -2.40000000000000012e149 or 2.8000000000000001e-37 < c

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto t \cdot \left(c \cdot \color{blue}{\left(i \cdot z - y2 \cdot y4\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - \color{blue}{y2 \cdot y4}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot \color{blue}{y4}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right) \]

      4. lower-*.f64 27.0

         \[\leadsto t \cdot \left(c \cdot \left(i \cdot z - y2 \cdot y4\right)\right) \]

   7. Applied rewrites 27.0%

      \[\leadsto t \cdot \left(c \cdot \color{blue}{\left(i \cdot z - y2 \cdot y4\right)}\right) \]

   if -2.40000000000000012e149 < c < -1.0499999999999999e-15

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -1.0499999999999999e-15 < c < -3.49999999999999991e-233

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if -3.49999999999999991e-233 < c < 6.9999999999999998e-297

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - \color{blue}{y3 \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

      4. lower-*.f64 26.9

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

   7. Applied rewrites 26.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   if 6.9999999999999998e-297 < c < 2.8000000000000001e-37

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 14: 31.3% accurate, 4.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -2.3 \cdot 10^{+149}:\\ \;\;\;\;a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.35 \cdot 10^{-212}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right)\\ \mathbf{elif}\;y3 \leq 4.5 \cdot 10^{-171}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right)\\ \mathbf{elif}\;y3 \leq 1.26 \cdot 10^{+79}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -2.3e+149)
   (* a (* y (- (* b x) (* y3 y5))))
   (if (<= y3 -1.35e-212)
     (* y2 (* y4 (- (* k y1) (* c t))))
     (if (<= y3 4.5e-171)
       (* b (* a (- (* x y) (* t z))))
       (if (<= y3 1.26e+79)
         (* x (* y2 (- (* c y0) (* a y1))))
         (* a (* y3 (- (* y1 z) (* y y5)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.3e+149) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -1.35e-212) {
		tmp = y2 * (y4 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y3 <= (-2.3d+149)) then
        tmp = a * (y * ((b * x) - (y3 * y5)))
    else if (y3 <= (-1.35d-212)) then
        tmp = y2 * (y4 * ((k * y1) - (c * t)))
    else if (y3 <= 4.5d-171) then
        tmp = b * (a * ((x * y) - (t * z)))
    else if (y3 <= 1.26d+79) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else
        tmp = a * (y3 * ((y1 * z) - (y * y5)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.3e+149) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else if (y3 <= -1.35e-212) {
		tmp = y2 * (y4 * ((k * y1) - (c * t)));
	} else if (y3 <= 4.5e-171) {
		tmp = b * (a * ((x * y) - (t * z)));
	} else if (y3 <= 1.26e+79) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y3 <= -2.3e+149:
		tmp = a * (y * ((b * x) - (y3 * y5)))
	elif y3 <= -1.35e-212:
		tmp = y2 * (y4 * ((k * y1) - (c * t)))
	elif y3 <= 4.5e-171:
		tmp = b * (a * ((x * y) - (t * z)))
	elif y3 <= 1.26e+79:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	else:
		tmp = a * (y3 * ((y1 * z) - (y * y5)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y3 <= -2.3e+149)
		tmp = Float64(a * Float64(y * Float64(Float64(b * x) - Float64(y3 * y5))));
	elseif (y3 <= -1.35e-212)
		tmp = Float64(y2 * Float64(y4 * Float64(Float64(k * y1) - Float64(c * t))));
	elseif (y3 <= 4.5e-171)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(t * z))));
	elseif (y3 <= 1.26e+79)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	else
		tmp = Float64(a * Float64(y3 * Float64(Float64(y1 * z) - Float64(y * y5))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y3 <= -2.3e+149)
		tmp = a * (y * ((b * x) - (y3 * y5)));
	elseif (y3 <= -1.35e-212)
		tmp = y2 * (y4 * ((k * y1) - (c * t)));
	elseif (y3 <= 4.5e-171)
		tmp = b * (a * ((x * y) - (t * z)));
	elseif (y3 <= 1.26e+79)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	else
		tmp = a * (y3 * ((y1 * z) - (y * y5)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y3, -2.3e+149], N[(a * N[(y * N[(N[(b * x), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.35e-212], N[(y2 * N[(y4 * N[(N[(k * y1), $MachinePrecision] - N[(c * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 4.5e-171], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.26e+79], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(y3 * N[(N[(y1 * z), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y3 < -2.2999999999999998e149

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - \color{blue}{y3 \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

      4. lower-*.f64 26.9

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

   7. Applied rewrites 26.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   if -2.2999999999999998e149 < y3 < -1.34999999999999991e-212

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto y2 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y1 - c \cdot t\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - \color{blue}{c \cdot t}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot \color{blue}{t}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

      5. lower-*.f64 26.6

         \[\leadsto y2 \cdot \left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto y2 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y1 - c \cdot t\right)\right)} \]

   if -1.34999999999999991e-212 < y3 < 4.5000000000000004e-171

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \color{blue}{\left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - \color{blue}{y0 \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

   4. Applied rewrites 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\mathsf{fma}\left(a, x \cdot y - t \cdot z, y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   5. Taylor expanded in a around inf

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

      1. lower-*.f64 N/A

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

      2. lower--.f64 N/A

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

      3. lower-*.f64 N/A

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

      4. lower-*.f64 26.4

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y - t \cdot z\right)\right) \]

   7. Applied rewrites 26.4%

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

   if 4.5000000000000004e-171 < y3 < 1.26e79

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.26e79 < y3

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 15: 31.3% accurate, 3.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{if}\;x \leq -6.8 \cdot 10^{+97}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq -1.85 \cdot 10^{-202}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq 5 \cdot 10^{-170}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq 3.5 \cdot 10^{-14}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{elif}\;x \leq 1.7 \cdot 10^{+278}:\\ \;\;\;\;a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (- (* b y4) (* i y5))))))
   (if (<= x -6.8e+97)
     (* x (* y2 (- (* c y0) (* a y1))))
     (if (<= x -1.85e-202)
       t_1
       (if (<= x 5e-170)
         (* c (* y4 (- (* y y3) (* t y2))))
         (if (<= x 3.5e-14)
           (* y3 (* y5 (- (* j y0) (* a y))))
           (if (<= x 1.7e+278) (* a (* y (- (* b x) (* y3 y5)))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double tmp;
	if (x <= -6.8e+97) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (x <= -1.85e-202) {
		tmp = t_1;
	} else if (x <= 5e-170) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (x <= 3.5e-14) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (x <= 1.7e+278) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else {
		tmp = t_1;
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (t * ((b * y4) - (i * y5)))
    if (x <= (-6.8d+97)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (x <= (-1.85d-202)) then
        tmp = t_1
    else if (x <= 5d-170) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (x <= 3.5d-14) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else if (x <= 1.7d+278) then
        tmp = a * (y * ((b * x) - (y3 * y5)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double tmp;
	if (x <= -6.8e+97) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (x <= -1.85e-202) {
		tmp = t_1;
	} else if (x <= 5e-170) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (x <= 3.5e-14) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (x <= 1.7e+278) {
		tmp = a * (y * ((b * x) - (y3 * y5)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (t * ((b * y4) - (i * y5)))
	tmp = 0
	if x <= -6.8e+97:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif x <= -1.85e-202:
		tmp = t_1
	elif x <= 5e-170:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif x <= 3.5e-14:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	elif x <= 1.7e+278:
		tmp = a * (y * ((b * x) - (y3 * y5)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))))
	tmp = 0.0
	if (x <= -6.8e+97)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (x <= -1.85e-202)
		tmp = t_1;
	elseif (x <= 5e-170)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (x <= 3.5e-14)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	elseif (x <= 1.7e+278)
		tmp = Float64(a * Float64(y * Float64(Float64(b * x) - Float64(y3 * y5))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (t * ((b * y4) - (i * y5)));
	tmp = 0.0;
	if (x <= -6.8e+97)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (x <= -1.85e-202)
		tmp = t_1;
	elseif (x <= 5e-170)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (x <= 3.5e-14)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	elseif (x <= 1.7e+278)
		tmp = a * (y * ((b * x) - (y3 * y5)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -6.8e+97], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.85e-202], t$95$1, If[LessEqual[x, 5e-170], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.5e-14], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.7e+278], N[(a * N[(y * N[(N[(b * x), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -6.8000000000000002e97

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -6.8000000000000002e97 < x < -1.84999999999999995e-202 or 1.7e278 < x

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4 - i \cdot y5\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - \color{blue}{i \cdot y5}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot \color{blue}{y5}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

      5. lower-*.f64 27.6

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   7. Applied rewrites 27.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.84999999999999995e-202 < x < 5.0000000000000001e-170

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      5. lower-*.f64 27.4

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.4%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]

   if 5.0000000000000001e-170 < x < 3.5000000000000002e-14

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if 3.5000000000000002e-14 < x < 1.7e278

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around inf

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - \color{blue}{y3 \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

      4. lower-*.f64 26.9

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right) \]

   7. Applied rewrites 26.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 16: 31.1% accurate, 3.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{if}\;y4 \leq -4 \cdot 10^{+19}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -7.3 \cdot 10^{-90}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq -5.5 \cdot 10^{-203}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq 1.9 \cdot 10^{-257}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 2.4 \cdot 10^{+187}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y3 (* y5 (- (* j y0) (* a y))))))
   (if (<= y4 -4e+19)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= y4 -7.3e-90)
       t_1
       (if (<= y4 -5.5e-203)
         (* y (* y5 (- (* i k) (* a y3))))
         (if (<= y4 1.9e-257)
           (* x (* y2 (- (* c y0) (* a y1))))
           (if (<= y4 2.4e+187) t_1 (* b (* y4 (- (* j t) (* k y)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y3 * (y5 * ((j * y0) - (a * y)));
	double tmp;
	if (y4 <= -4e+19) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (y4 <= -7.3e-90) {
		tmp = t_1;
	} else if (y4 <= -5.5e-203) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else if (y4 <= 1.9e-257) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y4 <= 2.4e+187) {
		tmp = t_1;
	} else {
		tmp = b * (y4 * ((j * t) - (k * y)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y3 * (y5 * ((j * y0) - (a * y)))
    if (y4 <= (-4d+19)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (y4 <= (-7.3d-90)) then
        tmp = t_1
    else if (y4 <= (-5.5d-203)) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else if (y4 <= 1.9d-257) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y4 <= 2.4d+187) then
        tmp = t_1
    else
        tmp = b * (y4 * ((j * t) - (k * y)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y3 * (y5 * ((j * y0) - (a * y)));
	double tmp;
	if (y4 <= -4e+19) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (y4 <= -7.3e-90) {
		tmp = t_1;
	} else if (y4 <= -5.5e-203) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else if (y4 <= 1.9e-257) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y4 <= 2.4e+187) {
		tmp = t_1;
	} else {
		tmp = b * (y4 * ((j * t) - (k * y)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y3 * (y5 * ((j * y0) - (a * y)))
	tmp = 0
	if y4 <= -4e+19:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif y4 <= -7.3e-90:
		tmp = t_1
	elif y4 <= -5.5e-203:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	elif y4 <= 1.9e-257:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y4 <= 2.4e+187:
		tmp = t_1
	else:
		tmp = b * (y4 * ((j * t) - (k * y)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))))
	tmp = 0.0
	if (y4 <= -4e+19)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (y4 <= -7.3e-90)
		tmp = t_1;
	elseif (y4 <= -5.5e-203)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (y4 <= 1.9e-257)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y4 <= 2.4e+187)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(y4 * Float64(Float64(j * t) - Float64(k * y))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y3 * (y5 * ((j * y0) - (a * y)));
	tmp = 0.0;
	if (y4 <= -4e+19)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (y4 <= -7.3e-90)
		tmp = t_1;
	elseif (y4 <= -5.5e-203)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	elseif (y4 <= 1.9e-257)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y4 <= 2.4e+187)
		tmp = t_1;
	else
		tmp = b * (y4 * ((j * t) - (k * y)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -4e+19], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -7.3e-90], t$95$1, If[LessEqual[y4, -5.5e-203], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.9e-257], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 2.4e+187], t$95$1, N[(b * N[(y4 * N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y4 < -4e19

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      5. lower-*.f64 27.4

         \[\leadsto c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.4%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]

   if -4e19 < y4 < -7.29999999999999998e-90 or 1.9000000000000002e-257 < y4 < 2.39999999999999985e187

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if -7.29999999999999998e-90 < y4 < -5.5000000000000002e-203

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]

   if -5.5000000000000002e-203 < y4 < 1.9000000000000002e-257

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 2.39999999999999985e187 < y4

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in b around inf

      \[\leadsto b \cdot \color{blue}{\left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \color{blue}{\left(j \cdot t - k \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - \color{blue}{k \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right) \]

      5. lower-*.f64 27.4

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right) \]

   7. Applied rewrites 27.4%

      \[\leadsto b \cdot \color{blue}{\left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 17: 30.7% accurate, 4.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y5 \leq -5.6 \cdot 10^{+63}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{elif}\;y5 \leq -1 \cdot 10^{-274}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 1.2 \cdot 10^{+92}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{+158}:\\ \;\;\;\;k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y5 -5.6e+63)
   (* y3 (* y5 (- (* j y0) (* a y))))
   (if (<= y5 -1e-274)
     (* x (* y2 (- (* c y0) (* a y1))))
     (if (<= y5 1.2e+92)
       (* b (* y4 (- (* j t) (* k y))))
       (if (<= y5 3.6e+158)
         (* k (* -1.0 (* y0 (* y2 y5))))
         (* y (* y5 (- (* i k) (* a y3)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -5.6e+63) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y5 <= -1e-274) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 1.2e+92) {
		tmp = b * (y4 * ((j * t) - (k * y)));
	} else if (y5 <= 3.6e+158) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y5 <= (-5.6d+63)) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else if (y5 <= (-1d-274)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 1.2d+92) then
        tmp = b * (y4 * ((j * t) - (k * y)))
    else if (y5 <= 3.6d+158) then
        tmp = k * ((-1.0d0) * (y0 * (y2 * y5)))
    else
        tmp = y * (y5 * ((i * k) - (a * y3)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -5.6e+63) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else if (y5 <= -1e-274) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 1.2e+92) {
		tmp = b * (y4 * ((j * t) - (k * y)));
	} else if (y5 <= 3.6e+158) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y5 <= -5.6e+63:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	elif y5 <= -1e-274:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 1.2e+92:
		tmp = b * (y4 * ((j * t) - (k * y)))
	elif y5 <= 3.6e+158:
		tmp = k * (-1.0 * (y0 * (y2 * y5)))
	else:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y5 <= -5.6e+63)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	elseif (y5 <= -1e-274)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 1.2e+92)
		tmp = Float64(b * Float64(y4 * Float64(Float64(j * t) - Float64(k * y))));
	elseif (y5 <= 3.6e+158)
		tmp = Float64(k * Float64(-1.0 * Float64(y0 * Float64(y2 * y5))));
	else
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y5 <= -5.6e+63)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	elseif (y5 <= -1e-274)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 1.2e+92)
		tmp = b * (y4 * ((j * t) - (k * y)));
	elseif (y5 <= 3.6e+158)
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	else
		tmp = y * (y5 * ((i * k) - (a * y3)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y5, -5.6e+63], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1e-274], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.2e+92], N[(b * N[(y4 * N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.6e+158], N[(k * N[(-1.0 * N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y5 < -5.59999999999999974e63

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if -5.59999999999999974e63 < y5 < -9.99999999999999966e-275

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -9.99999999999999966e-275 < y5 < 1.20000000000000002e92

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in b around inf

      \[\leadsto b \cdot \color{blue}{\left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \color{blue}{\left(j \cdot t - k \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - \color{blue}{k \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right) \]

      5. lower-*.f64 27.4

         \[\leadsto b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right) \]

   7. Applied rewrites 27.4%

      \[\leadsto b \cdot \color{blue}{\left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 1.20000000000000002e92 < y5 < 3.59999999999999988e158

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around 0

      \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot \color{blue}{y5}\right)\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

      3. lower-*.f64 17.2

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

   10. Applied rewrites 17.2%

       \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]

   if 3.59999999999999988e158 < y5

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
3. Recombined 5 regimes into one program.
4. Add Preprocessing

Alternative 18: 30.5% accurate, 4.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{if}\;y0 \leq -7.5 \cdot 10^{-77}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq -5 \cdot 10^{-298}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq 4.6 \cdot 10^{-232}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq 1.5 \cdot 10^{-100}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (- (* b y4) (* i y5))))))
   (if (<= y0 -7.5e-77)
     (* x (* y2 (- (* c y0) (* a y1))))
     (if (<= y0 -5e-298)
       t_1
       (if (<= y0 4.6e-232)
         (* y (* y5 (- (* i k) (* a y3))))
         (if (<= y0 1.5e-100) t_1 (* y3 (* y5 (- (* j y0) (* a y))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double tmp;
	if (y0 <= -7.5e-77) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y0 <= -5e-298) {
		tmp = t_1;
	} else if (y0 <= 4.6e-232) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else if (y0 <= 1.5e-100) {
		tmp = t_1;
	} else {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (t * ((b * y4) - (i * y5)))
    if (y0 <= (-7.5d-77)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y0 <= (-5d-298)) then
        tmp = t_1
    else if (y0 <= 4.6d-232) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else if (y0 <= 1.5d-100) then
        tmp = t_1
    else
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double tmp;
	if (y0 <= -7.5e-77) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y0 <= -5e-298) {
		tmp = t_1;
	} else if (y0 <= 4.6e-232) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else if (y0 <= 1.5e-100) {
		tmp = t_1;
	} else {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (t * ((b * y4) - (i * y5)))
	tmp = 0
	if y0 <= -7.5e-77:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y0 <= -5e-298:
		tmp = t_1
	elif y0 <= 4.6e-232:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	elif y0 <= 1.5e-100:
		tmp = t_1
	else:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))))
	tmp = 0.0
	if (y0 <= -7.5e-77)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y0 <= -5e-298)
		tmp = t_1;
	elseif (y0 <= 4.6e-232)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (y0 <= 1.5e-100)
		tmp = t_1;
	else
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (t * ((b * y4) - (i * y5)));
	tmp = 0.0;
	if (y0 <= -7.5e-77)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y0 <= -5e-298)
		tmp = t_1;
	elseif (y0 <= 4.6e-232)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	elseif (y0 <= 1.5e-100)
		tmp = t_1;
	else
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -7.5e-77], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -5e-298], t$95$1, If[LessEqual[y0, 4.6e-232], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.5e-100], t$95$1, N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -7.5000000000000006e-77

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \color{blue}{\left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - \color{blue}{j \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Applied rewrites 37.4%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(c \cdot y0 - a \cdot y1\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - \color{blue}{a \cdot y1}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot \color{blue}{y1}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

      5. lower-*.f64 27.2

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) \]

   7. Applied rewrites 27.2%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -7.5000000000000006e-77 < y0 < -5.0000000000000002e-298 or 4.6e-232 < y0 < 1.5e-100

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4 - i \cdot y5\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - \color{blue}{i \cdot y5}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot \color{blue}{y5}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

      5. lower-*.f64 27.6

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   7. Applied rewrites 27.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -5.0000000000000002e-298 < y0 < 4.6e-232

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]

   if 1.5e-100 < y0

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 19: 30.0% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -2.6 \cdot 10^{+108}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{+66}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -2.6e+108)
   (* y4 (* c (* -1.0 (* t y2))))
   (if (<= t 2.3e+66)
     (* y3 (* y5 (- (* j y0) (* a y))))
     (* j (* t (- (* b y4) (* i y5)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -2.6e+108) {
		tmp = y4 * (c * (-1.0 * (t * y2)));
	} else if (t <= 2.3e+66) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else {
		tmp = j * (t * ((b * y4) - (i * y5)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (t <= (-2.6d+108)) then
        tmp = y4 * (c * ((-1.0d0) * (t * y2)))
    else if (t <= 2.3d+66) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else
        tmp = j * (t * ((b * y4) - (i * y5)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -2.6e+108) {
		tmp = y4 * (c * (-1.0 * (t * y2)));
	} else if (t <= 2.3e+66) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else {
		tmp = j * (t * ((b * y4) - (i * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if t <= -2.6e+108:
		tmp = y4 * (c * (-1.0 * (t * y2)))
	elif t <= 2.3e+66:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	else:
		tmp = j * (t * ((b * y4) - (i * y5)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (t <= -2.6e+108)
		tmp = Float64(y4 * Float64(c * Float64(-1.0 * Float64(t * y2))));
	elseif (t <= 2.3e+66)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	else
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (t <= -2.6e+108)
		tmp = y4 * (c * (-1.0 * (t * y2)));
	elseif (t <= 2.3e+66)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	else
		tmp = j * (t * ((b * y4) - (i * y5)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -2.6e+108], N[(y4 * N[(c * N[(-1.0 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.3e+66], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if t < -2.6000000000000002e108

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      4. lower-*.f64 27.3

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.3%

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

      2. lower-*.f64 17.6

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

   10. Applied rewrites 17.6%

       \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]

   if -2.6000000000000002e108 < t < 2.3e66

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]

   if 2.3e66 < t

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto t \cdot \color{blue}{\left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - \color{blue}{y2 \cdot \left(c \cdot y4 - a \cdot y5\right)}\right) \]

   4. Applied rewrites 36.4%

      \[\leadsto \color{blue}{t \cdot \left(\mathsf{fma}\left(-1, z \cdot \left(a \cdot b - c \cdot i\right), j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   5. Taylor expanded in j around inf

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4 - i \cdot y5\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - \color{blue}{i \cdot y5}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot \color{blue}{y5}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

      5. lower-*.f64 27.6

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   7. Applied rewrites 27.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 20: 28.7% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right)\\ \mathbf{if}\;t \leq -2.6 \cdot 10^{+108}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 8.5 \cdot 10^{+194}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y4 (* c (* -1.0 (* t y2))))))
   (if (<= t -2.6e+108)
     t_1
     (if (<= t 8.5e+194) (* y3 (* y5 (- (* j y0) (* a y)))) t_1))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (c * (-1.0 * (t * y2)));
	double tmp;
	if (t <= -2.6e+108) {
		tmp = t_1;
	} else if (t <= 8.5e+194) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else {
		tmp = t_1;
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y4 * (c * ((-1.0d0) * (t * y2)))
    if (t <= (-2.6d+108)) then
        tmp = t_1
    else if (t <= 8.5d+194) then
        tmp = y3 * (y5 * ((j * y0) - (a * y)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (c * (-1.0 * (t * y2)));
	double tmp;
	if (t <= -2.6e+108) {
		tmp = t_1;
	} else if (t <= 8.5e+194) {
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y4 * (c * (-1.0 * (t * y2)))
	tmp = 0
	if t <= -2.6e+108:
		tmp = t_1
	elif t <= 8.5e+194:
		tmp = y3 * (y5 * ((j * y0) - (a * y)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y4 * Float64(c * Float64(-1.0 * Float64(t * y2))))
	tmp = 0.0
	if (t <= -2.6e+108)
		tmp = t_1;
	elseif (t <= 8.5e+194)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(a * y))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y4 * (c * (-1.0 * (t * y2)));
	tmp = 0.0;
	if (t <= -2.6e+108)
		tmp = t_1;
	elseif (t <= 8.5e+194)
		tmp = y3 * (y5 * ((j * y0) - (a * y)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y4 * N[(c * N[(-1.0 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.6e+108], t$95$1, If[LessEqual[t, 8.5e+194], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(a * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]

Derivation

1. Split input into 2 regimes

2. if t < -2.6000000000000002e108 or 8.50000000000000026e194 < t

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      4. lower-*.f64 27.3

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.3%

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

      2. lower-*.f64 17.6

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

   10. Applied rewrites 17.6%

       \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]

   if -2.6000000000000002e108 < t < 8.50000000000000026e194

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around -inf

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \color{blue}{\left(j \cdot y0 - a \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - \color{blue}{a \cdot y}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot \color{blue}{y}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

      5. lower-*.f64 26.5

         \[\leadsto y3 \cdot \left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right) \]

   7. Applied rewrites 26.5%

      \[\leadsto y3 \cdot \color{blue}{\left(y5 \cdot \left(j \cdot y0 - a \cdot y\right)\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 21: 28.3% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right)\\ \mathbf{if}\;y2 \leq -2.2 \cdot 10^{+261}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y2 \leq -1.05 \cdot 10^{-32}:\\ \;\;\;\;k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 2.7 \cdot 10^{+17}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y4 (* c (* -1.0 (* t y2))))))
   (if (<= y2 -2.2e+261)
     t_1
     (if (<= y2 -1.05e-32)
       (* k (* -1.0 (* y0 (* y2 y5))))
       (if (<= y2 2.7e+17) (* a (* y3 (* y1 z))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (c * (-1.0 * (t * y2)));
	double tmp;
	if (y2 <= -2.2e+261) {
		tmp = t_1;
	} else if (y2 <= -1.05e-32) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else if (y2 <= 2.7e+17) {
		tmp = a * (y3 * (y1 * z));
	} else {
		tmp = t_1;
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y4 * (c * ((-1.0d0) * (t * y2)))
    if (y2 <= (-2.2d+261)) then
        tmp = t_1
    else if (y2 <= (-1.05d-32)) then
        tmp = k * ((-1.0d0) * (y0 * (y2 * y5)))
    else if (y2 <= 2.7d+17) then
        tmp = a * (y3 * (y1 * z))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (c * (-1.0 * (t * y2)));
	double tmp;
	if (y2 <= -2.2e+261) {
		tmp = t_1;
	} else if (y2 <= -1.05e-32) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else if (y2 <= 2.7e+17) {
		tmp = a * (y3 * (y1 * z));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y4 * (c * (-1.0 * (t * y2)))
	tmp = 0
	if y2 <= -2.2e+261:
		tmp = t_1
	elif y2 <= -1.05e-32:
		tmp = k * (-1.0 * (y0 * (y2 * y5)))
	elif y2 <= 2.7e+17:
		tmp = a * (y3 * (y1 * z))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y4 * Float64(c * Float64(-1.0 * Float64(t * y2))))
	tmp = 0.0
	if (y2 <= -2.2e+261)
		tmp = t_1;
	elseif (y2 <= -1.05e-32)
		tmp = Float64(k * Float64(-1.0 * Float64(y0 * Float64(y2 * y5))));
	elseif (y2 <= 2.7e+17)
		tmp = Float64(a * Float64(y3 * Float64(y1 * z)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y4 * (c * (-1.0 * (t * y2)));
	tmp = 0.0;
	if (y2 <= -2.2e+261)
		tmp = t_1;
	elseif (y2 <= -1.05e-32)
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	elseif (y2 <= 2.7e+17)
		tmp = a * (y3 * (y1 * z));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y4 * N[(c * N[(-1.0 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -2.2e+261], t$95$1, If[LessEqual[y2, -1.05e-32], N[(k * N[(-1.0 * N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 2.7e+17], N[(a * N[(y3 * N[(y1 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if y2 < -2.19999999999999984e261 or 2.7e17 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      4. lower-*.f64 27.3

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.3%

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

      2. lower-*.f64 17.6

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

   10. Applied rewrites 17.6%

       \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]

   if -2.19999999999999984e261 < y2 < -1.05e-32

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around 0

      \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot \color{blue}{y5}\right)\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

      3. lower-*.f64 17.2

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

   10. Applied rewrites 17.2%

       \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]

   if -1.05e-32 < y2 < 2.7e17

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 22: 22.9% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right)\\ \mathbf{if}\;t \leq -3.2 \cdot 10^{+118}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 4.2 \cdot 10^{+190}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y4 (* c (* -1.0 (* t y2))))))
   (if (<= t -3.2e+118)
     t_1
     (if (<= t 4.2e+190) (* y (* y5 (- (* i k) (* a y3)))) t_1))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (c * (-1.0 * (t * y2)));
	double tmp;
	if (t <= -3.2e+118) {
		tmp = t_1;
	} else if (t <= 4.2e+190) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = t_1;
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y4 * (c * ((-1.0d0) * (t * y2)))
    if (t <= (-3.2d+118)) then
        tmp = t_1
    else if (t <= 4.2d+190) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (c * (-1.0 * (t * y2)));
	double tmp;
	if (t <= -3.2e+118) {
		tmp = t_1;
	} else if (t <= 4.2e+190) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y4 * (c * (-1.0 * (t * y2)))
	tmp = 0
	if t <= -3.2e+118:
		tmp = t_1
	elif t <= 4.2e+190:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y4 * Float64(c * Float64(-1.0 * Float64(t * y2))))
	tmp = 0.0
	if (t <= -3.2e+118)
		tmp = t_1;
	elseif (t <= 4.2e+190)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y4 * (c * (-1.0 * (t * y2)));
	tmp = 0.0;
	if (t <= -3.2e+118)
		tmp = t_1;
	elseif (t <= 4.2e+190)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y4 * N[(c * N[(-1.0 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.2e+118], t$95$1, If[LessEqual[t, 4.2e+190], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]

Derivation

1. Split input into 2 regimes

2. if t < -3.20000000000000016e118 or 4.2000000000000001e190 < t

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in c around inf

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - \color{blue}{t \cdot y2}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot \color{blue}{y2}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

      4. lower-*.f64 27.3

         \[\leadsto y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) \]

   7. Applied rewrites 27.3%

      \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y \cdot y3 - t \cdot y2\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

      2. lower-*.f64 17.6

         \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot y2\right)\right)\right) \]

   10. Applied rewrites 17.6%

       \[\leadsto y4 \cdot \left(c \cdot \left(-1 \cdot \left(t \cdot \color{blue}{y2}\right)\right)\right) \]

   if -3.20000000000000016e118 < t < 4.2000000000000001e190

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 23: 22.2% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.05 \cdot 10^{-32}:\\ \;\;\;\;k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 9.6 \cdot 10^{+17}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right)\\ \mathbf{elif}\;y2 \leq 4.8 \cdot 10^{+183}:\\ \;\;\;\;-1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.05e-32)
   (* k (* -1.0 (* y0 (* y2 y5))))
   (if (<= y2 9.6e+17)
     (* a (* y3 (* y1 z)))
     (if (<= y2 4.8e+183)
       (* -1.0 (* a (* y (* y3 y5))))
       (* k (* y5 (* -1.0 (* y0 y2))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.05e-32) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else if (y2 <= 9.6e+17) {
		tmp = a * (y3 * (y1 * z));
	} else if (y2 <= 4.8e+183) {
		tmp = -1.0 * (a * (y * (y3 * y5)));
	} else {
		tmp = k * (y5 * (-1.0 * (y0 * y2)));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y2 <= (-1.05d-32)) then
        tmp = k * ((-1.0d0) * (y0 * (y2 * y5)))
    else if (y2 <= 9.6d+17) then
        tmp = a * (y3 * (y1 * z))
    else if (y2 <= 4.8d+183) then
        tmp = (-1.0d0) * (a * (y * (y3 * y5)))
    else
        tmp = k * (y5 * ((-1.0d0) * (y0 * y2)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.05e-32) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else if (y2 <= 9.6e+17) {
		tmp = a * (y3 * (y1 * z));
	} else if (y2 <= 4.8e+183) {
		tmp = -1.0 * (a * (y * (y3 * y5)));
	} else {
		tmp = k * (y5 * (-1.0 * (y0 * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y2 <= -1.05e-32:
		tmp = k * (-1.0 * (y0 * (y2 * y5)))
	elif y2 <= 9.6e+17:
		tmp = a * (y3 * (y1 * z))
	elif y2 <= 4.8e+183:
		tmp = -1.0 * (a * (y * (y3 * y5)))
	else:
		tmp = k * (y5 * (-1.0 * (y0 * y2)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y2 <= -1.05e-32)
		tmp = Float64(k * Float64(-1.0 * Float64(y0 * Float64(y2 * y5))));
	elseif (y2 <= 9.6e+17)
		tmp = Float64(a * Float64(y3 * Float64(y1 * z)));
	elseif (y2 <= 4.8e+183)
		tmp = Float64(-1.0 * Float64(a * Float64(y * Float64(y3 * y5))));
	else
		tmp = Float64(k * Float64(y5 * Float64(-1.0 * Float64(y0 * y2))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y2 <= -1.05e-32)
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	elseif (y2 <= 9.6e+17)
		tmp = a * (y3 * (y1 * z));
	elseif (y2 <= 4.8e+183)
		tmp = -1.0 * (a * (y * (y3 * y5)));
	else
		tmp = k * (y5 * (-1.0 * (y0 * y2)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y2, -1.05e-32], N[(k * N[(-1.0 * N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 9.6e+17], N[(a * N[(y3 * N[(y1 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.8e+183], N[(-1.0 * N[(a * N[(y * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(y5 * N[(-1.0 * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y2 < -1.05e-32

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around 0

      \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot \color{blue}{y5}\right)\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

      3. lower-*.f64 17.2

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

   10. Applied rewrites 17.2%

       \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]

   if -1.05e-32 < y2 < 9.6e17

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   if 9.6e17 < y2 < 4.8000000000000003e183

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]

   8. Taylor expanded in a around inf

      \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot \color{blue}{y3}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot y3\right)\right)\right) \]

      2. lower-*.f64 17.0

         \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot y3\right)\right)\right) \]

   10. Applied rewrites 17.0%

       \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot \color{blue}{y3}\right)\right)\right) \]

   11. Taylor expanded in a around inf

       \[\leadsto -1 \cdot \left(a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right)}\right) \]
   12. Step-by-step derivation

       1. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \color{blue}{\left(y3 \cdot y5\right)}\right)\right) \]

       2. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot \color{blue}{y5}\right)\right)\right) \]

       3. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right) \]

       4. lower-*.f64 17.1

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right) \]

   13. Applied rewrites 17.1%

       \[\leadsto -1 \cdot \left(a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right)}\right) \]

   if 4.8000000000000003e183 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around 0

      \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{y2}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right)\right)\right) \]

      2. lower-*.f64 17.3

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right)\right)\right) \]

   10. Applied rewrites 17.3%

       \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{y2}\right)\right)\right) \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 24: 22.0% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.05 \cdot 10^{-32}:\\ \;\;\;\;k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 9.6 \cdot 10^{+17}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right)\\ \mathbf{elif}\;y2 \leq 4.9 \cdot 10^{+191}:\\ \;\;\;\;-1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.05e-32)
   (* k (* -1.0 (* y0 (* y2 y5))))
   (if (<= y2 9.6e+17)
     (* a (* y3 (* y1 z)))
     (if (<= y2 4.9e+191)
       (* -1.0 (* a (* y (* y3 y5))))
       (* y1 (* y4 (* k y2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.05e-32) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else if (y2 <= 9.6e+17) {
		tmp = a * (y3 * (y1 * z));
	} else if (y2 <= 4.9e+191) {
		tmp = -1.0 * (a * (y * (y3 * y5)));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y2 <= (-1.05d-32)) then
        tmp = k * ((-1.0d0) * (y0 * (y2 * y5)))
    else if (y2 <= 9.6d+17) then
        tmp = a * (y3 * (y1 * z))
    else if (y2 <= 4.9d+191) then
        tmp = (-1.0d0) * (a * (y * (y3 * y5)))
    else
        tmp = y1 * (y4 * (k * y2))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.05e-32) {
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	} else if (y2 <= 9.6e+17) {
		tmp = a * (y3 * (y1 * z));
	} else if (y2 <= 4.9e+191) {
		tmp = -1.0 * (a * (y * (y3 * y5)));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y2 <= -1.05e-32:
		tmp = k * (-1.0 * (y0 * (y2 * y5)))
	elif y2 <= 9.6e+17:
		tmp = a * (y3 * (y1 * z))
	elif y2 <= 4.9e+191:
		tmp = -1.0 * (a * (y * (y3 * y5)))
	else:
		tmp = y1 * (y4 * (k * y2))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y2 <= -1.05e-32)
		tmp = Float64(k * Float64(-1.0 * Float64(y0 * Float64(y2 * y5))));
	elseif (y2 <= 9.6e+17)
		tmp = Float64(a * Float64(y3 * Float64(y1 * z)));
	elseif (y2 <= 4.9e+191)
		tmp = Float64(-1.0 * Float64(a * Float64(y * Float64(y3 * y5))));
	else
		tmp = Float64(y1 * Float64(y4 * Float64(k * y2)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y2 <= -1.05e-32)
		tmp = k * (-1.0 * (y0 * (y2 * y5)));
	elseif (y2 <= 9.6e+17)
		tmp = a * (y3 * (y1 * z));
	elseif (y2 <= 4.9e+191)
		tmp = -1.0 * (a * (y * (y3 * y5)));
	else
		tmp = y1 * (y4 * (k * y2));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y2, -1.05e-32], N[(k * N[(-1.0 * N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 9.6e+17], N[(a * N[(y3 * N[(y1 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.9e+191], N[(-1.0 * N[(a * N[(y * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(y4 * N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y2 < -1.05e-32

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around 0

      \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot \color{blue}{y5}\right)\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

      3. lower-*.f64 17.2

         \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right) \]

   10. Applied rewrites 17.2%

       \[\leadsto k \cdot \left(-1 \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot y5\right)}\right)\right) \]

   if -1.05e-32 < y2 < 9.6e17

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   if 9.6e17 < y2 < 4.9e191

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]

   8. Taylor expanded in a around inf

      \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot \color{blue}{y3}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot y3\right)\right)\right) \]

      2. lower-*.f64 17.0

         \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot y3\right)\right)\right) \]

   10. Applied rewrites 17.0%

       \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot \color{blue}{y3}\right)\right)\right) \]

   11. Taylor expanded in a around inf

       \[\leadsto -1 \cdot \left(a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right)}\right) \]
   12. Step-by-step derivation

       1. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \color{blue}{\left(y3 \cdot y5\right)}\right)\right) \]

       2. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot \color{blue}{y5}\right)\right)\right) \]

       3. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right) \]

       4. lower-*.f64 17.1

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right) \]

   13. Applied rewrites 17.1%

       \[\leadsto -1 \cdot \left(a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right)}\right) \]

   if 4.9e191 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 25: 21.6% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+119}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 9.6 \cdot 10^{+17}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right)\\ \mathbf{elif}\;y2 \leq 4.9 \cdot 10^{+191}:\\ \;\;\;\;-1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.15e+119)
   (* y1 (* k (* y2 y4)))
   (if (<= y2 9.6e+17)
     (* a (* y3 (* y1 z)))
     (if (<= y2 4.9e+191)
       (* -1.0 (* a (* y (* y3 y5))))
       (* y1 (* y4 (* k y2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.15e+119) {
		tmp = y1 * (k * (y2 * y4));
	} else if (y2 <= 9.6e+17) {
		tmp = a * (y3 * (y1 * z));
	} else if (y2 <= 4.9e+191) {
		tmp = -1.0 * (a * (y * (y3 * y5)));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y2 <= (-1.15d+119)) then
        tmp = y1 * (k * (y2 * y4))
    else if (y2 <= 9.6d+17) then
        tmp = a * (y3 * (y1 * z))
    else if (y2 <= 4.9d+191) then
        tmp = (-1.0d0) * (a * (y * (y3 * y5)))
    else
        tmp = y1 * (y4 * (k * y2))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.15e+119) {
		tmp = y1 * (k * (y2 * y4));
	} else if (y2 <= 9.6e+17) {
		tmp = a * (y3 * (y1 * z));
	} else if (y2 <= 4.9e+191) {
		tmp = -1.0 * (a * (y * (y3 * y5)));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y2 <= -1.15e+119:
		tmp = y1 * (k * (y2 * y4))
	elif y2 <= 9.6e+17:
		tmp = a * (y3 * (y1 * z))
	elif y2 <= 4.9e+191:
		tmp = -1.0 * (a * (y * (y3 * y5)))
	else:
		tmp = y1 * (y4 * (k * y2))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y2 <= -1.15e+119)
		tmp = Float64(y1 * Float64(k * Float64(y2 * y4)));
	elseif (y2 <= 9.6e+17)
		tmp = Float64(a * Float64(y3 * Float64(y1 * z)));
	elseif (y2 <= 4.9e+191)
		tmp = Float64(-1.0 * Float64(a * Float64(y * Float64(y3 * y5))));
	else
		tmp = Float64(y1 * Float64(y4 * Float64(k * y2)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y2 <= -1.15e+119)
		tmp = y1 * (k * (y2 * y4));
	elseif (y2 <= 9.6e+17)
		tmp = a * (y3 * (y1 * z));
	elseif (y2 <= 4.9e+191)
		tmp = -1.0 * (a * (y * (y3 * y5)));
	else
		tmp = y1 * (y4 * (k * y2));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y2, -1.15e+119], N[(y1 * N[(k * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 9.6e+17], N[(a * N[(y3 * N[(y1 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.9e+191], N[(-1.0 * N[(a * N[(y * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(y4 * N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y2 < -1.15e119

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

      2. lower-*.f64 17.3

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

   10. Applied rewrites 17.3%

       \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]

   if -1.15e119 < y2 < 9.6e17

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   if 9.6e17 < y2 < 4.9e191

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]

   8. Taylor expanded in a around inf

      \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot \color{blue}{y3}\right)\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot y3\right)\right)\right) \]

      2. lower-*.f64 17.0

         \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot y3\right)\right)\right) \]

   10. Applied rewrites 17.0%

       \[\leadsto y \cdot \left(y5 \cdot \left(-1 \cdot \left(a \cdot \color{blue}{y3}\right)\right)\right) \]

   11. Taylor expanded in a around inf

       \[\leadsto -1 \cdot \left(a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right)}\right) \]
   12. Step-by-step derivation

       1. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \color{blue}{\left(y3 \cdot y5\right)}\right)\right) \]

       2. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot \color{blue}{y5}\right)\right)\right) \]

       3. lower-*.f64 N/A

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right) \]

       4. lower-*.f64 17.1

          \[\leadsto -1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right) \]

   13. Applied rewrites 17.1%

       \[\leadsto -1 \cdot \left(a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right)}\right) \]

   if 4.9e191 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
3. Recombined 4 regimes into one program.
4. Add Preprocessing

Alternative 26: 21.4% accurate, 7.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+119}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 2.85 \cdot 10^{-7}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.15e+119)
   (* y1 (* k (* y2 y4)))
   (if (<= y2 2.85e-7) (* a (* y3 (* y1 z))) (* y1 (* y4 (* k y2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.15e+119) {
		tmp = y1 * (k * (y2 * y4));
	} else if (y2 <= 2.85e-7) {
		tmp = a * (y3 * (y1 * z));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y2 <= (-1.15d+119)) then
        tmp = y1 * (k * (y2 * y4))
    else if (y2 <= 2.85d-7) then
        tmp = a * (y3 * (y1 * z))
    else
        tmp = y1 * (y4 * (k * y2))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.15e+119) {
		tmp = y1 * (k * (y2 * y4));
	} else if (y2 <= 2.85e-7) {
		tmp = a * (y3 * (y1 * z));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y2 <= -1.15e+119:
		tmp = y1 * (k * (y2 * y4))
	elif y2 <= 2.85e-7:
		tmp = a * (y3 * (y1 * z))
	else:
		tmp = y1 * (y4 * (k * y2))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y2 <= -1.15e+119)
		tmp = Float64(y1 * Float64(k * Float64(y2 * y4)));
	elseif (y2 <= 2.85e-7)
		tmp = Float64(a * Float64(y3 * Float64(y1 * z)));
	else
		tmp = Float64(y1 * Float64(y4 * Float64(k * y2)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y2 <= -1.15e+119)
		tmp = y1 * (k * (y2 * y4));
	elseif (y2 <= 2.85e-7)
		tmp = a * (y3 * (y1 * z));
	else
		tmp = y1 * (y4 * (k * y2));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y2, -1.15e+119], N[(y1 * N[(k * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 2.85e-7], N[(a * N[(y3 * N[(y1 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(y4 * N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if y2 < -1.15e119

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

      2. lower-*.f64 17.3

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

   10. Applied rewrites 17.3%

       \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]

   if -1.15e119 < y2 < 2.8500000000000002e-7

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z\right)\right) \]

   if 2.8500000000000002e-7 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 27: 21.0% accurate, 7.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+119}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 2.85 \cdot 10^{-7}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.15e+119)
   (* y1 (* k (* y2 y4)))
   (if (<= y2 2.85e-7) (* a (* y1 (* y3 z))) (* y1 (* y4 (* k y2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.15e+119) {
		tmp = y1 * (k * (y2 * y4));
	} else if (y2 <= 2.85e-7) {
		tmp = a * (y1 * (y3 * z));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y2 <= (-1.15d+119)) then
        tmp = y1 * (k * (y2 * y4))
    else if (y2 <= 2.85d-7) then
        tmp = a * (y1 * (y3 * z))
    else
        tmp = y1 * (y4 * (k * y2))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -1.15e+119) {
		tmp = y1 * (k * (y2 * y4));
	} else if (y2 <= 2.85e-7) {
		tmp = a * (y1 * (y3 * z));
	} else {
		tmp = y1 * (y4 * (k * y2));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y2 <= -1.15e+119:
		tmp = y1 * (k * (y2 * y4))
	elif y2 <= 2.85e-7:
		tmp = a * (y1 * (y3 * z))
	else:
		tmp = y1 * (y4 * (k * y2))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y2 <= -1.15e+119)
		tmp = Float64(y1 * Float64(k * Float64(y2 * y4)));
	elseif (y2 <= 2.85e-7)
		tmp = Float64(a * Float64(y1 * Float64(y3 * z)));
	else
		tmp = Float64(y1 * Float64(y4 * Float64(k * y2)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y2 <= -1.15e+119)
		tmp = y1 * (k * (y2 * y4));
	elseif (y2 <= 2.85e-7)
		tmp = a * (y1 * (y3 * z));
	else
		tmp = y1 * (y4 * (k * y2));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y2, -1.15e+119], N[(y1 * N[(k * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 2.85e-7], N[(a * N[(y1 * N[(y3 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(y4 * N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if y2 < -1.15e119

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

      2. lower-*.f64 17.3

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

   10. Applied rewrites 17.3%

       \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]

   if -1.15e119 < y2 < 2.8500000000000002e-7

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - \color{blue}{-1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   4. Applied rewrites 35.9%

      \[\leadsto \color{blue}{a \cdot \left(\mathsf{fma}\left(-1, y1 \cdot \left(x \cdot y2 - y3 \cdot z\right), b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y3 around inf

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - \color{blue}{y \cdot y5}\right)\right) \]

      2. lower--.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot \color{blue}{y5}\right)\right) \]

      3. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

      4. lower-*.f64 26.6

         \[\leadsto a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right) \]

   7. Applied rewrites 26.6%

      \[\leadsto a \cdot \left(y3 \cdot \color{blue}{\left(y1 \cdot z - y \cdot y5\right)}\right) \]

   8. Taylor expanded in y around 0

      \[\leadsto a \cdot \left(y1 \cdot \left(y3 \cdot \color{blue}{z}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right) \]

      2. lower-*.f64 17.3

         \[\leadsto a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right) \]

   10. Applied rewrites 17.3%

       \[\leadsto a \cdot \left(y1 \cdot \left(y3 \cdot \color{blue}{z}\right)\right) \]

   if 2.8500000000000002e-7 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 17.1

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]

   10. Applied rewrites 17.1%

       \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2\right)\right) \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 28: 18.0% accurate, 9.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 1.35 \cdot 10^{-112}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b 1.35e-112) (* i (* k (* y y5))) (* y1 (* k (* y2 y4)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= 1.35e-112) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = y1 * (k * (y2 * y4));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (b <= 1.35d-112) then
        tmp = i * (k * (y * y5))
    else
        tmp = y1 * (k * (y2 * y4))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= 1.35e-112) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = y1 * (k * (y2 * y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if b <= 1.35e-112:
		tmp = i * (k * (y * y5))
	else:
		tmp = y1 * (k * (y2 * y4))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (b <= 1.35e-112)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(y1 * Float64(k * Float64(y2 * y4)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (b <= 1.35e-112)
		tmp = i * (k * (y * y5));
	else
		tmp = y1 * (k * (y2 * y4));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[b, 1.35e-112], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(k * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 1.35e-112

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around inf

      \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

      3. lower-*.f64 16.8

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

   10. Applied rewrites 16.8%

       \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]

   if 1.35e-112 < b

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

      2. lower-*.f64 17.3

         \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot y4\right)\right) \]

   10. Applied rewrites 17.3%

       \[\leadsto y1 \cdot \left(k \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 29: 17.0% accurate, 9.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 1.35 \cdot 10^{-112}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b 1.35e-112) (* i (* k (* y y5))) (* k (* y1 (* y2 y4)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= 1.35e-112) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = k * (y1 * (y2 * y4));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (b <= 1.35d-112) then
        tmp = i * (k * (y * y5))
    else
        tmp = k * (y1 * (y2 * y4))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= 1.35e-112) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = k * (y1 * (y2 * y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if b <= 1.35e-112:
		tmp = i * (k * (y * y5))
	else:
		tmp = k * (y1 * (y2 * y4))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (b <= 1.35e-112)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(k * Float64(y1 * Float64(y2 * y4)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (b <= 1.35e-112)
		tmp = i * (k * (y * y5));
	else
		tmp = k * (y1 * (y2 * y4));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[b, 1.35e-112], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(y1 * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 1.35e-112

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around inf

      \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

      3. lower-*.f64 16.8

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

   10. Applied rewrites 16.8%

       \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]

   if 1.35e-112 < b

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y4 \cdot \color{blue}{\left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. lower--.f64 N/A

         \[\leadsto y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{c \cdot \left(t \cdot y2 - y \cdot y3\right)}\right) \]

   4. Applied rewrites 37.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\mathsf{fma}\left(b, j \cdot t - k \cdot y, y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in y1 around inf

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \color{blue}{\left(k \cdot y2 - j \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - \color{blue}{j \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto y1 \cdot \color{blue}{\left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   8. Taylor expanded in j around 0

      \[\leadsto k \cdot \left(y1 \cdot \color{blue}{\left(y2 \cdot y4\right)}\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y1 \cdot \left(y2 \cdot \color{blue}{y4}\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right) \]

      3. lower-*.f64 17.5

         \[\leadsto k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right) \]

   10. Applied rewrites 17.5%

       \[\leadsto k \cdot \left(y1 \cdot \color{blue}{\left(y2 \cdot y4\right)}\right) \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 30: 17.0% accurate, 9.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq -2.4 \cdot 10^{+140}:\\ \;\;\;\;y \cdot \left(i \cdot \left(k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(i \cdot \left(y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= k -2.4e+140) (* y (* i (* k y5))) (* k (* i (* y y5)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -2.4e+140) {
		tmp = y * (i * (k * y5));
	} else {
		tmp = k * (i * (y * y5));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (k <= (-2.4d+140)) then
        tmp = y * (i * (k * y5))
    else
        tmp = k * (i * (y * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -2.4e+140) {
		tmp = y * (i * (k * y5));
	} else {
		tmp = k * (i * (y * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if k <= -2.4e+140:
		tmp = y * (i * (k * y5))
	else:
		tmp = k * (i * (y * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (k <= -2.4e+140)
		tmp = Float64(y * Float64(i * Float64(k * y5)));
	else
		tmp = Float64(k * Float64(i * Float64(y * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (k <= -2.4e+140)
		tmp = y * (i * (k * y5));
	else
		tmp = k * (i * (y * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[k, -2.4e+140], N[(y * N[(i * N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(i * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if k < -2.4e140

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in y around -inf

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \color{blue}{\left(i \cdot k - a \cdot y3\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - \color{blue}{a \cdot y3}\right)\right) \]

      3. lower--.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot \color{blue}{y3}\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

      5. lower-*.f64 26.3

         \[\leadsto y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \]

   7. Applied rewrites 26.3%

      \[\leadsto y \cdot \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]

   8. Taylor expanded in a around 0

      \[\leadsto y \cdot \left(i \cdot \left(k \cdot \color{blue}{y5}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto y \cdot \left(i \cdot \left(k \cdot y5\right)\right) \]

      2. lower-*.f64 16.8

         \[\leadsto y \cdot \left(i \cdot \left(k \cdot y5\right)\right) \]

   10. Applied rewrites 16.8%

       \[\leadsto y \cdot \left(i \cdot \left(k \cdot \color{blue}{y5}\right)\right) \]

   if -2.4e140 < k

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around inf

      \[\leadsto k \cdot \left(i \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(i \cdot \left(y \cdot y5\right)\right) \]

      2. lower-*.f64 17.2

         \[\leadsto k \cdot \left(i \cdot \left(y \cdot y5\right)\right) \]

   10. Applied rewrites 17.2%

       \[\leadsto k \cdot \left(i \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 31: 16.9% accurate, 9.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -7.8 \cdot 10^{-19}:\\ \;\;\;\;i \cdot \left(\left(k \cdot y\right) \cdot y5\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(i \cdot \left(y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -7.8e-19) (* i (* (* k y) y5)) (* k (* i (* y y5)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -7.8e-19) {
		tmp = i * ((k * y) * y5);
	} else {
		tmp = k * (i * (y * y5));
	}
	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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y2 <= (-7.8d-19)) then
        tmp = i * ((k * y) * y5)
    else
        tmp = k * (i * (y * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y2 <= -7.8e-19) {
		tmp = i * ((k * y) * y5);
	} else {
		tmp = k * (i * (y * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y2 <= -7.8e-19:
		tmp = i * ((k * y) * y5)
	else:
		tmp = k * (i * (y * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y2 <= -7.8e-19)
		tmp = Float64(i * Float64(Float64(k * y) * y5));
	else
		tmp = Float64(k * Float64(i * Float64(y * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y2 <= -7.8e-19)
		tmp = i * ((k * y) * y5);
	else
		tmp = k * (i * (y * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y2, -7.8e-19], N[(i * N[(N[(k * y), $MachinePrecision] * y5), $MachinePrecision]), $MachinePrecision], N[(k * N[(i * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y2 < -7.7999999999999999e-19

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around inf

      \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]

      2. lower-*.f64 N/A

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

      3. lower-*.f64 16.8

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

   10. Applied rewrites 16.8%

       \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]
   11. Step-by-step derivation

       1. lift-*.f64 N/A

          \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

       2. lift-*.f64 N/A

          \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

       3. associate-*r* N/A

          \[\leadsto i \cdot \left(\left(k \cdot y\right) \cdot y5\right) \]

       4. lower-*.f64 N/A

          \[\leadsto i \cdot \left(\left(k \cdot y\right) \cdot y5\right) \]

       5. lower-*.f64 16.7

          \[\leadsto i \cdot \left(\left(k \cdot y\right) \cdot y5\right) \]

   12. Applied rewrites 16.7%

       \[\leadsto i \cdot \left(\left(k \cdot y\right) \cdot y5\right) \]

   if -7.7999999999999999e-19 < y2

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y5 around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

      3. lower--.f64 N/A

         \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

   4. Applied rewrites 37.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   5. Taylor expanded in k around -inf

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

      2. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

      3. lower-fma.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

      4. lower-*.f64 N/A

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

      5. lower-*.f64 26.7

         \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   7. Applied rewrites 26.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

   8. Taylor expanded in y around inf

      \[\leadsto k \cdot \left(i \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]
   9. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto k \cdot \left(i \cdot \left(y \cdot y5\right)\right) \]

      2. lower-*.f64 17.2

         \[\leadsto k \cdot \left(i \cdot \left(y \cdot y5\right)\right) \]

   10. Applied rewrites 17.2%

       \[\leadsto k \cdot \left(i \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 32: 16.8% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* i (* k (* y y5))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return i * (k * (y * y5));
}

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, c, i, j, k, y0, y1, y2, y3, y4, y5)
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), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = i * (k * (y * y5))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return i * (k * (y * y5));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return i * (k * (y * y5))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(i * Float64(k * Float64(y * y5)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = i * (k * (y * y5));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 28.8%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in y5 around -inf

   \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
3. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   2. lower-*.f64 N/A

      \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)}\right) \]

   3. lower--.f64 N/A

      \[\leadsto -1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - \color{blue}{a \cdot \left(t \cdot y2 - y \cdot y3\right)}\right)\right) \]

4. Applied rewrites 37.1%

   \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\mathsf{fma}\left(i, j \cdot t - k \cdot y, y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

5. Taylor expanded in k around -inf

   \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
6. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)}\right) \]

   2. lower-*.f64 N/A

      \[\leadsto k \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + \color{blue}{i \cdot y}\right)\right) \]

   3. lower-fma.f64 N/A

      \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot \color{blue}{y2}, i \cdot y\right)\right) \]

   4. lower-*.f64 N/A

      \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

   5. lower-*.f64 26.7

      \[\leadsto k \cdot \left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right) \]

7. Applied rewrites 26.7%

   \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \mathsf{fma}\left(-1, y0 \cdot y2, i \cdot y\right)\right)} \]

8. Taylor expanded in y around inf

   \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]
9. Step-by-step derivation

   1. lower-*.f64 N/A

      \[\leadsto i \cdot \left(k \cdot \left(y \cdot \color{blue}{y5}\right)\right) \]

   2. lower-*.f64 N/A

      \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

   3. lower-*.f64 16.8

      \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5\right)\right) \]

10. Applied rewrites 16.8%

    \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y \cdot y5\right)}\right) \]
11. Add Preprocessing

Reproduce

herbie shell --seed 2025155 
(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
  :name "Linear.Matrix:det44 from linear-1.19.1.3"
  :precision binary64
  (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i)))) (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a)))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))