quadm (p42, negative)

Percentage Accurate: 52.5% → 85.5%

Time: 4.1s

Alternatives: 10

Speedup: 2.6×

Specification

Math

\[\begin{array}{l} \\ \frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (/ (- (- b) (sqrt (- (* b b) (* 4.0 (* a c))))) (* 2.0 a)))

C

double code(double a, double b, double c) {
	return (-b - sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a);
}

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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    code = (-b - sqrt(((b * b) - (4.0d0 * (a * c))))) / (2.0d0 * a)
end function

Java

public static double code(double a, double b, double c) {
	return (-b - Math.sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a);
}

Python

def code(a, b, c):
	return (-b - math.sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a)

Julia

function code(a, b, c)
	return Float64(Float64(Float64(-b) - sqrt(Float64(Float64(b * b) - Float64(4.0 * Float64(a * c))))) / Float64(2.0 * a))
end

MATLAB

function tmp = code(a, b, c)
	tmp = (-b - sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a);
end

Wolfram

code[a_, b_, c_] := N[(N[((-b) - N[Sqrt[N[(N[(b * b), $MachinePrecision] - N[(4.0 * N[(a * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[(2.0 * a), $MachinePrecision]), $MachinePrecision]

Initial Program: 52.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (/ (- (- b) (sqrt (- (* b b) (* 4.0 (* a c))))) (* 2.0 a)))

C

double code(double a, double b, double c) {
	return (-b - sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a);
}

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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    code = (-b - sqrt(((b * b) - (4.0d0 * (a * c))))) / (2.0d0 * a)
end function

Java

public static double code(double a, double b, double c) {
	return (-b - Math.sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a);
}

Python

def code(a, b, c):
	return (-b - math.sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a)

Julia

function code(a, b, c)
	return Float64(Float64(Float64(-b) - sqrt(Float64(Float64(b * b) - Float64(4.0 * Float64(a * c))))) / Float64(2.0 * a))
end

MATLAB

function tmp = code(a, b, c)
	tmp = (-b - sqrt(((b * b) - (4.0 * (a * c))))) / (2.0 * a);
end

Wolfram

code[a_, b_, c_] := N[(N[((-b) - N[Sqrt[N[(N[(b * b), $MachinePrecision] - N[(4.0 * N[(a * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[(2.0 * a), $MachinePrecision]), $MachinePrecision]

Alternative 1: 85.5% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.5 \cdot 10^{-37}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 10^{+108}:\\ \;\;\;\;-0.5 \cdot \frac{b}{a} - \frac{\sqrt{\mathsf{fma}\left(a \cdot -4, c, b \cdot b\right)}}{a + a}\\ \mathbf{else}:\\ \;\;\;\;\frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.5e-37)
   (- (/ c b))
   (if (<= b 1e+108)
     (- (* -0.5 (/ b a)) (/ (sqrt (fma (* a -4.0) c (* b b))) (+ a a)))
     (/ (- b) a))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.5e-37) {
		tmp = -(c / b);
	} else if (b <= 1e+108) {
		tmp = (-0.5 * (b / a)) - (sqrt(fma((a * -4.0), c, (b * b))) / (a + a));
	} else {
		tmp = -b / a;
	}
	return tmp;
}

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.5e-37)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 1e+108)
		tmp = Float64(Float64(-0.5 * Float64(b / a)) - Float64(sqrt(fma(Float64(a * -4.0), c, Float64(b * b))) / Float64(a + a)));
	else
		tmp = Float64(Float64(-b) / a);
	end
	return tmp
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.5e-37], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 1e+108], N[(N[(-0.5 * N[(b / a), $MachinePrecision]), $MachinePrecision] - N[(N[Sqrt[N[(N[(a * -4.0), $MachinePrecision] * c + N[(b * b), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[(a + a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[((-b) / a), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.5000000000000004e-37

   1. Initial program 15.2%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 88.7

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 88.7%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.5000000000000004e-37 < b < 1e108

   1. Initial program 78.4%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{b \cdot b} - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

      2. lift--.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{b \cdot b - 4 \cdot \left(a \cdot c\right)}}}{2 \cdot a} \]

      3. pow2 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{{b}^{2}} - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

      4. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{{b}^{2} - \color{blue}{4 \cdot \left(a \cdot c\right)}}}{2 \cdot a} \]

      5. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{{b}^{2} - 4 \cdot \color{blue}{\left(a \cdot c\right)}}}{2 \cdot a} \]

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

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{{b}^{2} + \left(\mathsf{neg}\left(4\right)\right) \cdot \left(a \cdot c\right)}}}{2 \cdot a} \]

      7. metadata-eval N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{{b}^{2} + \color{blue}{-4} \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

      8. +-commutative N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{-4 \cdot \left(a \cdot c\right) + {b}^{2}}}}{2 \cdot a} \]

      9. associate-*r* N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\left(-4 \cdot a\right) \cdot c} + {b}^{2}}}{2 \cdot a} \]

      10. lower-fma.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\mathsf{fma}\left(-4 \cdot a, c, {b}^{2}\right)}}}{2 \cdot a} \]

      11. lower-*.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(\color{blue}{-4 \cdot a}, c, {b}^{2}\right)}}{2 \cdot a} \]

      12. pow2 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, \color{blue}{b \cdot b}\right)}}{2 \cdot a} \]

      13. lift-*.f64 78.5

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, \color{blue}{b \cdot b}\right)}}{2 \cdot a} \]

      14. lift-*.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{2 \cdot a}} \]

      15. count-2-rev N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{a + a}} \]

      16. lower-+.f64 78.5

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{a + a}} \]

   3. Applied rewrites 78.5%

      \[\leadsto \color{blue}{\frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{a + a}} \]
   4. Step-by-step derivation

      1. lift-+.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{a + a}} \]

      2. lift-/.f64 N/A

         \[\leadsto \color{blue}{\frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{a + a}} \]

      3. lift--.f64 N/A

         \[\leadsto \frac{\color{blue}{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}}{a + a} \]

      4. lift-sqrt.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \color{blue}{\sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}}{a + a} \]

      5. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(\color{blue}{-4 \cdot a}, c, b \cdot b\right)}}{a + a} \]

      6. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, \color{blue}{b \cdot b}\right)}}{a + a} \]

      7. lift-fma.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\left(-4 \cdot a\right) \cdot c + b \cdot b}}}{a + a} \]

      8. div-sub N/A

         \[\leadsto \color{blue}{\frac{-b}{a + a} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{a + a}} \]

      9. count-2-rev N/A

         \[\leadsto \frac{-b}{\color{blue}{2 \cdot a}} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{a + a} \]

      10. lower--.f64 N/A

          \[\leadsto \color{blue}{\frac{-b}{2 \cdot a} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{a + a}} \]

      11. lower-/.f64 N/A

          \[\leadsto \color{blue}{\frac{-b}{2 \cdot a}} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{a + a} \]

      12. count-2-rev N/A

          \[\leadsto \frac{-b}{\color{blue}{a + a}} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{a + a} \]

      13. lift-+.f64 N/A

          \[\leadsto \frac{-b}{\color{blue}{a + a}} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{a + a} \]

      14. count-2-rev N/A

          \[\leadsto \frac{-b}{a + a} - \frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{\color{blue}{2 \cdot a}} \]

      15. lower-/.f64 N/A

          \[\leadsto \frac{-b}{a + a} - \color{blue}{\frac{\sqrt{\left(-4 \cdot a\right) \cdot c + b \cdot b}}{2 \cdot a}} \]

   5. Applied rewrites 78.5%

      \[\leadsto \color{blue}{\frac{-b}{a + a} - \frac{\sqrt{\mathsf{fma}\left(a \cdot -4, c, b \cdot b\right)}}{a + a}} \]

   6. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\frac{-1}{2} \cdot \frac{b}{a}} - \frac{\sqrt{\mathsf{fma}\left(a \cdot -4, c, b \cdot b\right)}}{a + a} \]
   7. Step-by-step derivation

      1. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\frac{b}{a}} - \frac{\sqrt{\mathsf{fma}\left(a \cdot -4, c, b \cdot b\right)}}{a + a} \]

      2. lower-/.f64 78.5

         \[\leadsto -0.5 \cdot \frac{b}{\color{blue}{a}} - \frac{\sqrt{\mathsf{fma}\left(a \cdot -4, c, b \cdot b\right)}}{a + a} \]

   8. Applied rewrites 78.5%

      \[\leadsto \color{blue}{-0.5 \cdot \frac{b}{a}} - \frac{\sqrt{\mathsf{fma}\left(a \cdot -4, c, b \cdot b\right)}}{a + a} \]

   if 1e108 < b

   1. Initial program 52.9%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. associate-*r/ N/A

         \[\leadsto \frac{-1 \cdot b}{\color{blue}{a}} \]

      2. mul-1-neg N/A

         \[\leadsto \frac{\mathsf{neg}\left(b\right)}{a} \]

      3. lift-neg.f64 N/A

         \[\leadsto \frac{-b}{a} \]

      4. lower-/.f64 96.4

         \[\leadsto \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 96.4%

      \[\leadsto \color{blue}{\frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 2: 85.5% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.5 \cdot 10^{-37}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 10^{+108}:\\ \;\;\;\;\frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(b, b, \left(a \cdot -4\right) \cdot c\right)}}{a + a}\\ \mathbf{else}:\\ \;\;\;\;\frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.5e-37)
   (- (/ c b))
   (if (<= b 1e+108)
     (/ (- (- b) (sqrt (fma b b (* (* a -4.0) c)))) (+ a a))
     (/ (- b) a))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.5e-37) {
		tmp = -(c / b);
	} else if (b <= 1e+108) {
		tmp = (-b - sqrt(fma(b, b, ((a * -4.0) * c)))) / (a + a);
	} else {
		tmp = -b / a;
	}
	return tmp;
}

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.5e-37)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 1e+108)
		tmp = Float64(Float64(Float64(-b) - sqrt(fma(b, b, Float64(Float64(a * -4.0) * c)))) / Float64(a + a));
	else
		tmp = Float64(Float64(-b) / a);
	end
	return tmp
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.5e-37], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 1e+108], N[(N[((-b) - N[Sqrt[N[(b * b + N[(N[(a * -4.0), $MachinePrecision] * c), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[(a + a), $MachinePrecision]), $MachinePrecision], N[((-b) / a), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.5000000000000004e-37

   1. Initial program 15.2%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 88.7

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 88.7%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.5000000000000004e-37 < b < 1e108

   1. Initial program 78.4%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]
   2. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{b \cdot b} - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

      2. lift--.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{b \cdot b - 4 \cdot \left(a \cdot c\right)}}}{2 \cdot a} \]

      3. pow2 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{{b}^{2}} - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

      4. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{{b}^{2} - \color{blue}{4 \cdot \left(a \cdot c\right)}}}{2 \cdot a} \]

      5. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{{b}^{2} - 4 \cdot \color{blue}{\left(a \cdot c\right)}}}{2 \cdot a} \]

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

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{{b}^{2} + \left(\mathsf{neg}\left(4\right)\right) \cdot \left(a \cdot c\right)}}}{2 \cdot a} \]

      7. metadata-eval N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{{b}^{2} + \color{blue}{-4} \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

      8. +-commutative N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{-4 \cdot \left(a \cdot c\right) + {b}^{2}}}}{2 \cdot a} \]

      9. associate-*r* N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\left(-4 \cdot a\right) \cdot c} + {b}^{2}}}{2 \cdot a} \]

      10. lower-fma.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\mathsf{fma}\left(-4 \cdot a, c, {b}^{2}\right)}}}{2 \cdot a} \]

      11. lower-*.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(\color{blue}{-4 \cdot a}, c, {b}^{2}\right)}}{2 \cdot a} \]

      12. pow2 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, \color{blue}{b \cdot b}\right)}}{2 \cdot a} \]

      13. lift-*.f64 78.5

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, \color{blue}{b \cdot b}\right)}}{2 \cdot a} \]

      14. lift-*.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{2 \cdot a}} \]

      15. count-2-rev N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{a + a}} \]

      16. lower-+.f64 78.5

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{\color{blue}{a + a}} \]

   3. Applied rewrites 78.5%

      \[\leadsto \color{blue}{\frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, b \cdot b\right)}}{a + a}} \]
   4. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(\color{blue}{-4 \cdot a}, c, b \cdot b\right)}}{a + a} \]

      2. lift-*.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(-4 \cdot a, c, \color{blue}{b \cdot b}\right)}}{a + a} \]

      3. lift-fma.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\left(-4 \cdot a\right) \cdot c + b \cdot b}}}{a + a} \]

      4. pow2 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\left(-4 \cdot a\right) \cdot c + \color{blue}{{b}^{2}}}}{a + a} \]

      5. associate-*r* N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{-4 \cdot \left(a \cdot c\right)} + {b}^{2}}}{a + a} \]

      6. +-commutative N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{{b}^{2} + -4 \cdot \left(a \cdot c\right)}}}{a + a} \]

      7. pow2 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{b \cdot b} + -4 \cdot \left(a \cdot c\right)}}{a + a} \]

      8. lower-fma.f64 N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\mathsf{fma}\left(b, b, -4 \cdot \left(a \cdot c\right)\right)}}}{a + a} \]

      9. associate-*r* N/A

         \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(b, b, \color{blue}{\left(-4 \cdot a\right) \cdot c}\right)}}{a + a} \]

      10. lower-*.f64 N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(b, b, \color{blue}{\left(-4 \cdot a\right) \cdot c}\right)}}{a + a} \]

      11. *-commutative N/A

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(b, b, \color{blue}{\left(a \cdot -4\right)} \cdot c\right)}}{a + a} \]

      12. lower-*.f64 78.5

          \[\leadsto \frac{\left(-b\right) - \sqrt{\mathsf{fma}\left(b, b, \color{blue}{\left(a \cdot -4\right)} \cdot c\right)}}{a + a} \]

   5. Applied rewrites 78.5%

      \[\leadsto \frac{\left(-b\right) - \sqrt{\color{blue}{\mathsf{fma}\left(b, b, \left(a \cdot -4\right) \cdot c\right)}}}{a + a} \]

   if 1e108 < b

   1. Initial program 52.9%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. associate-*r/ N/A

         \[\leadsto \frac{-1 \cdot b}{\color{blue}{a}} \]

      2. mul-1-neg N/A

         \[\leadsto \frac{\mathsf{neg}\left(b\right)}{a} \]

      3. lift-neg.f64 N/A

         \[\leadsto \frac{-b}{a} \]

      4. lower-/.f64 96.4

         \[\leadsto \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 96.4%

      \[\leadsto \color{blue}{\frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 3: 80.9% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.8 \cdot 10^{-38}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 3.4 \cdot 10^{-93}:\\ \;\;\;\;-0.5 \cdot \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a}\\ \mathbf{else}:\\ \;\;\;\;\frac{c}{b} + \frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.8e-38)
   (- (/ c b))
   (if (<= b 3.4e-93)
     (* -0.5 (/ (+ (sqrt (* (* a -4.0) c)) b) a))
     (+ (/ c b) (/ (- b) a)))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.8e-38) {
		tmp = -(c / b);
	} else if (b <= 3.4e-93) {
		tmp = -0.5 * ((sqrt(((a * -4.0) * c)) + b) / a);
	} else {
		tmp = (c / b) + (-b / a);
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-4.8d-38)) then
        tmp = -(c / b)
    else if (b <= 3.4d-93) then
        tmp = (-0.5d0) * ((sqrt(((a * (-4.0d0)) * c)) + b) / a)
    else
        tmp = (c / b) + (-b / a)
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.8e-38) {
		tmp = -(c / b);
	} else if (b <= 3.4e-93) {
		tmp = -0.5 * ((Math.sqrt(((a * -4.0) * c)) + b) / a);
	} else {
		tmp = (c / b) + (-b / a);
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -4.8e-38:
		tmp = -(c / b)
	elif b <= 3.4e-93:
		tmp = -0.5 * ((math.sqrt(((a * -4.0) * c)) + b) / a)
	else:
		tmp = (c / b) + (-b / a)
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.8e-38)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 3.4e-93)
		tmp = Float64(-0.5 * Float64(Float64(sqrt(Float64(Float64(a * -4.0) * c)) + b) / a));
	else
		tmp = Float64(Float64(c / b) + Float64(Float64(-b) / a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -4.8e-38)
		tmp = -(c / b);
	elseif (b <= 3.4e-93)
		tmp = -0.5 * ((sqrt(((a * -4.0) * c)) + b) / a);
	else
		tmp = (c / b) + (-b / a);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.8e-38], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 3.4e-93], N[(-0.5 * N[(N[(N[Sqrt[N[(N[(a * -4.0), $MachinePrecision] * c), $MachinePrecision]], $MachinePrecision] + b), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], N[(N[(c / b), $MachinePrecision] + N[((-b) / a), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.80000000000000044e-38

   1. Initial program 15.2%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 88.7

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 88.7%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.80000000000000044e-38 < b < 3.40000000000000001e-93

   1. Initial program 71.7%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{\frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4}\right) + \frac{-1}{2} \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. distribute-lft-out N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \frac{b}{a}\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \frac{b}{a}\right)} \]

      3. lower-+.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \color{blue}{\frac{b}{a}}\right) \]

      4. sqrt-unprod N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      5. lower-sqrt.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      6. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      7. lower-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      8. lower-/.f64 32.8

         \[\leadsto -0.5 \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{\color{blue}{a}}\right) \]

   4. Applied rewrites 32.8%

      \[\leadsto \color{blue}{-0.5 \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right)} \]

   5. Taylor expanded in a around 0

      \[\leadsto \frac{-1}{2} \cdot \frac{b + \sqrt{a \cdot c} \cdot \sqrt{-4}}{\color{blue}{a}} \]
   6. Step-by-step derivation

      1. lower-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{b + \sqrt{a \cdot c} \cdot \sqrt{-4}}{a} \]

      2. +-commutative N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{a \cdot c} \cdot \sqrt{-4} + b}{a} \]

      3. lower-+.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{a \cdot c} \cdot \sqrt{-4} + b}{a} \]

      4. sqrt-unprod N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{\left(a \cdot c\right) \cdot -4} + b}{a} \]

      5. *-commutative N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{-4 \cdot \left(a \cdot c\right)} + b}{a} \]

      6. lower-sqrt.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{-4 \cdot \left(a \cdot c\right)} + b}{a} \]

      7. associate-*r* N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \]

      8. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \]

      9. *-commutative N/A

         \[\leadsto \frac{-1}{2} \cdot \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \]

      10. lower-*.f64 67.6

          \[\leadsto -0.5 \cdot \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \]

   7. Applied rewrites 67.6%

      \[\leadsto -0.5 \cdot \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{\color{blue}{a}} \]

   if 3.40000000000000001e-93 < b

   1. Initial program 69.9%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in c around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a} + \frac{c}{b}} \]
   3. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      2. lower-+.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      3. lower-/.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1} \cdot \frac{b}{a} \]

      4. associate-*r/ N/A

         \[\leadsto \frac{c}{b} + \frac{-1 \cdot b}{\color{blue}{a}} \]

      5. mul-1-neg N/A

         \[\leadsto \frac{c}{b} + \frac{\mathsf{neg}\left(b\right)}{a} \]

      6. lift-neg.f64 N/A

         \[\leadsto \frac{c}{b} + \frac{-b}{a} \]

      7. lower-/.f64 84.4

         \[\leadsto \frac{c}{b} + \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 84.4%

      \[\leadsto \color{blue}{\frac{c}{b} + \frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 4: 80.6% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.8 \cdot 10^{-38}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 1.12 \cdot 10^{-95}:\\ \;\;\;\;-\left(-\sqrt{\frac{\frac{-1}{a}}{c}}\right) \cdot c\\ \mathbf{else}:\\ \;\;\;\;\frac{c}{b} + \frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.8e-38)
   (- (/ c b))
   (if (<= b 1.12e-95)
     (- (* (- (sqrt (/ (/ -1.0 a) c))) c))
     (+ (/ c b) (/ (- b) a)))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.8e-38) {
		tmp = -(c / b);
	} else if (b <= 1.12e-95) {
		tmp = -(-sqrt(((-1.0 / a) / c)) * c);
	} else {
		tmp = (c / b) + (-b / a);
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-4.8d-38)) then
        tmp = -(c / b)
    else if (b <= 1.12d-95) then
        tmp = -(-sqrt((((-1.0d0) / a) / c)) * c)
    else
        tmp = (c / b) + (-b / a)
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.8e-38) {
		tmp = -(c / b);
	} else if (b <= 1.12e-95) {
		tmp = -(-Math.sqrt(((-1.0 / a) / c)) * c);
	} else {
		tmp = (c / b) + (-b / a);
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -4.8e-38:
		tmp = -(c / b)
	elif b <= 1.12e-95:
		tmp = -(-math.sqrt(((-1.0 / a) / c)) * c)
	else:
		tmp = (c / b) + (-b / a)
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.8e-38)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 1.12e-95)
		tmp = Float64(-Float64(Float64(-sqrt(Float64(Float64(-1.0 / a) / c))) * c));
	else
		tmp = Float64(Float64(c / b) + Float64(Float64(-b) / a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -4.8e-38)
		tmp = -(c / b);
	elseif (b <= 1.12e-95)
		tmp = -(-sqrt(((-1.0 / a) / c)) * c);
	else
		tmp = (c / b) + (-b / a);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.8e-38], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 1.12e-95], (-N[((-N[Sqrt[N[(N[(-1.0 / a), $MachinePrecision] / c), $MachinePrecision]], $MachinePrecision]) * c), $MachinePrecision]), N[(N[(c / b), $MachinePrecision] + N[((-b) / a), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.80000000000000044e-38

   1. Initial program 15.2%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 88.7

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 88.7%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.80000000000000044e-38 < b < 1.12000000000000006e-95

   1. Initial program 71.6%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in c around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(c \cdot \left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right)\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -c \cdot \left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right) \]

      3. *-commutative N/A

         \[\leadsto -\left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right) \cdot c \]

      4. lower-*.f64 N/A

         \[\leadsto -\left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right) \cdot c \]

   4. Applied rewrites 66.0%

      \[\leadsto \color{blue}{-\mathsf{fma}\left(\frac{b}{c \cdot a}, 0.5, -\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c} \]

   5. Taylor expanded in a around inf

      \[\leadsto -\left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right)\right) \cdot c \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right)\right) \cdot c \]

      2. *-commutative N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a}} \cdot \sqrt{-1}\right)\right) \cdot c \]

      3. sqrt-prod N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      4. lift-/.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      5. lift-*.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      6. lift-*.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      7. lift-sqrt.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      8. lift-neg.f64 66.2

         \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      9. lift-*.f64 N/A

         \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      10. lift-*.f64 N/A

          \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      11. lift-/.f64 N/A

          \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      12. associate-*l/ N/A

          \[\leadsto -\left(-\sqrt{\frac{1 \cdot -1}{c \cdot a}}\right) \cdot c \]

      13. metadata-eval N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

      14. *-commutative N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{a \cdot c}}\right) \cdot c \]

      15. lower-/.f64 N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{a \cdot c}}\right) \cdot c \]

      16. *-commutative N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

      17. lift-*.f64 66.2

          \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

   7. Applied rewrites 66.2%

      \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]
   8. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

      2. *-commutative N/A

         \[\leadsto -\left(-\sqrt{\frac{-1}{a \cdot c}}\right) \cdot c \]

      3. lower-/.f64 N/A

         \[\leadsto -\left(-\sqrt{\frac{-1}{a \cdot c}}\right) \cdot c \]

      4. associate-/r* N/A

         \[\leadsto -\left(-\sqrt{\frac{\frac{-1}{a}}{c}}\right) \cdot c \]

      5. lower-/.f64 N/A

         \[\leadsto -\left(-\sqrt{\frac{\frac{-1}{a}}{c}}\right) \cdot c \]

      6. lower-/.f64 66.7

         \[\leadsto -\left(-\sqrt{\frac{\frac{-1}{a}}{c}}\right) \cdot c \]

   9. Applied rewrites 66.7%

      \[\leadsto -\left(-\sqrt{\frac{\frac{-1}{a}}{c}}\right) \cdot c \]

   if 1.12000000000000006e-95 < b

   1. Initial program 69.9%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in c around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a} + \frac{c}{b}} \]
   3. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      2. lower-+.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      3. lower-/.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1} \cdot \frac{b}{a} \]

      4. associate-*r/ N/A

         \[\leadsto \frac{c}{b} + \frac{-1 \cdot b}{\color{blue}{a}} \]

      5. mul-1-neg N/A

         \[\leadsto \frac{c}{b} + \frac{\mathsf{neg}\left(b\right)}{a} \]

      6. lift-neg.f64 N/A

         \[\leadsto \frac{c}{b} + \frac{-b}{a} \]

      7. lower-/.f64 84.3

         \[\leadsto \frac{c}{b} + \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 84.3%

      \[\leadsto \color{blue}{\frac{c}{b} + \frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 5: 80.4% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.8 \cdot 10^{-38}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 1.12 \cdot 10^{-95}:\\ \;\;\;\;-\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c\\ \mathbf{else}:\\ \;\;\;\;\frac{c}{b} + \frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.8e-38)
   (- (/ c b))
   (if (<= b 1.12e-95)
     (- (* (- (sqrt (/ -1.0 (* c a)))) c))
     (+ (/ c b) (/ (- b) a)))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.8e-38) {
		tmp = -(c / b);
	} else if (b <= 1.12e-95) {
		tmp = -(-sqrt((-1.0 / (c * a))) * c);
	} else {
		tmp = (c / b) + (-b / a);
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-4.8d-38)) then
        tmp = -(c / b)
    else if (b <= 1.12d-95) then
        tmp = -(-sqrt(((-1.0d0) / (c * a))) * c)
    else
        tmp = (c / b) + (-b / a)
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.8e-38) {
		tmp = -(c / b);
	} else if (b <= 1.12e-95) {
		tmp = -(-Math.sqrt((-1.0 / (c * a))) * c);
	} else {
		tmp = (c / b) + (-b / a);
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -4.8e-38:
		tmp = -(c / b)
	elif b <= 1.12e-95:
		tmp = -(-math.sqrt((-1.0 / (c * a))) * c)
	else:
		tmp = (c / b) + (-b / a)
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.8e-38)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 1.12e-95)
		tmp = Float64(-Float64(Float64(-sqrt(Float64(-1.0 / Float64(c * a)))) * c));
	else
		tmp = Float64(Float64(c / b) + Float64(Float64(-b) / a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -4.8e-38)
		tmp = -(c / b);
	elseif (b <= 1.12e-95)
		tmp = -(-sqrt((-1.0 / (c * a))) * c);
	else
		tmp = (c / b) + (-b / a);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.8e-38], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 1.12e-95], (-N[((-N[Sqrt[N[(-1.0 / N[(c * a), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]) * c), $MachinePrecision]), N[(N[(c / b), $MachinePrecision] + N[((-b) / a), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.80000000000000044e-38

   1. Initial program 15.2%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 88.7

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 88.7%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.80000000000000044e-38 < b < 1.12000000000000006e-95

   1. Initial program 71.6%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in c around -inf

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(c \cdot \left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right)\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -c \cdot \left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right) \]

      3. *-commutative N/A

         \[\leadsto -\left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right) \cdot c \]

      4. lower-*.f64 N/A

         \[\leadsto -\left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right) + \frac{1}{2} \cdot \frac{b}{a \cdot c}\right) \cdot c \]

   4. Applied rewrites 66.0%

      \[\leadsto \color{blue}{-\mathsf{fma}\left(\frac{b}{c \cdot a}, 0.5, -\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c} \]

   5. Taylor expanded in a around inf

      \[\leadsto -\left(-1 \cdot \left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right)\right) \cdot c \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{a \cdot c}} \cdot \sqrt{-1}\right)\right) \cdot c \]

      2. *-commutative N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a}} \cdot \sqrt{-1}\right)\right) \cdot c \]

      3. sqrt-prod N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      4. lift-/.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      5. lift-*.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      6. lift-*.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      7. lift-sqrt.f64 N/A

         \[\leadsto -\left(\mathsf{neg}\left(\sqrt{\frac{1}{c \cdot a} \cdot -1}\right)\right) \cdot c \]

      8. lift-neg.f64 66.2

         \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      9. lift-*.f64 N/A

         \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      10. lift-*.f64 N/A

          \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      11. lift-/.f64 N/A

          \[\leadsto -\left(-\sqrt{\frac{1}{c \cdot a} \cdot -1}\right) \cdot c \]

      12. associate-*l/ N/A

          \[\leadsto -\left(-\sqrt{\frac{1 \cdot -1}{c \cdot a}}\right) \cdot c \]

      13. metadata-eval N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

      14. *-commutative N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{a \cdot c}}\right) \cdot c \]

      15. lower-/.f64 N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{a \cdot c}}\right) \cdot c \]

      16. *-commutative N/A

          \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

      17. lift-*.f64 66.2

          \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

   7. Applied rewrites 66.2%

      \[\leadsto -\left(-\sqrt{\frac{-1}{c \cdot a}}\right) \cdot c \]

   if 1.12000000000000006e-95 < b

   1. Initial program 69.9%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in c around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a} + \frac{c}{b}} \]
   3. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      2. lower-+.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      3. lower-/.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1} \cdot \frac{b}{a} \]

      4. associate-*r/ N/A

         \[\leadsto \frac{c}{b} + \frac{-1 \cdot b}{\color{blue}{a}} \]

      5. mul-1-neg N/A

         \[\leadsto \frac{c}{b} + \frac{\mathsf{neg}\left(b\right)}{a} \]

      6. lift-neg.f64 N/A

         \[\leadsto \frac{c}{b} + \frac{-b}{a} \]

      7. lower-/.f64 84.3

         \[\leadsto \frac{c}{b} + \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 84.3%

      \[\leadsto \color{blue}{\frac{c}{b} + \frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 6: 72.0% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.2 \cdot 10^{-171}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 1.95 \cdot 10^{-144}:\\ \;\;\;\;-\sqrt{\frac{-c}{a}}\\ \mathbf{else}:\\ \;\;\;\;\frac{c}{b} + \frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.2e-171)
   (- (/ c b))
   (if (<= b 1.95e-144) (- (sqrt (/ (- c) a))) (+ (/ c b) (/ (- b) a)))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.2e-171) {
		tmp = -(c / b);
	} else if (b <= 1.95e-144) {
		tmp = -sqrt((-c / a));
	} else {
		tmp = (c / b) + (-b / a);
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-4.2d-171)) then
        tmp = -(c / b)
    else if (b <= 1.95d-144) then
        tmp = -sqrt((-c / a))
    else
        tmp = (c / b) + (-b / a)
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.2e-171) {
		tmp = -(c / b);
	} else if (b <= 1.95e-144) {
		tmp = -Math.sqrt((-c / a));
	} else {
		tmp = (c / b) + (-b / a);
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -4.2e-171:
		tmp = -(c / b)
	elif b <= 1.95e-144:
		tmp = -math.sqrt((-c / a))
	else:
		tmp = (c / b) + (-b / a)
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.2e-171)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 1.95e-144)
		tmp = Float64(-sqrt(Float64(Float64(-c) / a)));
	else
		tmp = Float64(Float64(c / b) + Float64(Float64(-b) / a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -4.2e-171)
		tmp = -(c / b);
	elseif (b <= 1.95e-144)
		tmp = -sqrt((-c / a));
	else
		tmp = (c / b) + (-b / a);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.2e-171], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 1.95e-144], (-N[Sqrt[N[((-c) / a), $MachinePrecision]], $MachinePrecision]), N[(N[(c / b), $MachinePrecision] + N[((-b) / a), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.2e-171

   1. Initial program 24.7%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 77.9

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 77.9%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.2e-171 < b < 1.95000000000000007e-144

   1. Initial program 74.8%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{\frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4}\right) + \frac{-1}{2} \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. distribute-lft-out N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \frac{b}{a}\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \frac{b}{a}\right)} \]

      3. lower-+.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \color{blue}{\frac{b}{a}}\right) \]

      4. sqrt-unprod N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      5. lower-sqrt.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      6. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      7. lower-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      8. lower-/.f64 37.7

         \[\leadsto -0.5 \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{\color{blue}{a}}\right) \]

   4. Applied rewrites 37.7%

      \[\leadsto \color{blue}{-0.5 \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right)} \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right)} \]

      2. lift-+.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \color{blue}{\frac{b}{a}}\right) \]

      3. lift-sqrt.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      5. lift-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      6. lift-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{\color{blue}{a}}\right) \]

      7. *-commutative N/A

         \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \color{blue}{\frac{-1}{2}} \]

      8. lower-*.f64 N/A

         \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \color{blue}{\frac{-1}{2}} \]

      9. lift-/.f64 N/A

         \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      10. lift-*.f64 N/A

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      11. lift-sqrt.f64 N/A

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      12. lift-/.f64 N/A

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      13. lift-+.f64 37.7

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot -0.5 \]

   6. Applied rewrites 37.7%

      \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \color{blue}{-0.5} \]

   7. Taylor expanded in a around 0

      \[\leadsto \frac{b + \sqrt{a \cdot c} \cdot \sqrt{-4}}{a} \cdot \frac{-1}{2} \]
   8. Step-by-step derivation

      1. lower-/.f64 N/A

         \[\leadsto \frac{b + \sqrt{a \cdot c} \cdot \sqrt{-4}}{a} \cdot \frac{-1}{2} \]

      2. +-commutative N/A

         \[\leadsto \frac{\sqrt{a \cdot c} \cdot \sqrt{-4} + b}{a} \cdot \frac{-1}{2} \]

      3. lower-+.f64 N/A

         \[\leadsto \frac{\sqrt{a \cdot c} \cdot \sqrt{-4} + b}{a} \cdot \frac{-1}{2} \]

      4. sqrt-unprod N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot c\right) \cdot -4} + b}{a} \cdot \frac{-1}{2} \]

      5. *-commutative N/A

         \[\leadsto \frac{\sqrt{-4 \cdot \left(a \cdot c\right)} + b}{a} \cdot \frac{-1}{2} \]

      6. associate-*r* N/A

         \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      7. *-commutative N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      8. lift-*.f64 N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      9. lift-*.f64 N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      10. lift-sqrt.f64 74.3

          \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot -0.5 \]

      11. lift-*.f64 N/A

          \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      12. *-commutative N/A

          \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      13. lower-*.f64 74.3

          \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot -0.5 \]

   9. Applied rewrites 74.3%

      \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot -0.5 \]

   10. Taylor expanded in a around -inf

       \[\leadsto -1 \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-1}\right)} \]
   11. Step-by-step derivation

       1. mul-1-neg N/A

          \[\leadsto \mathsf{neg}\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-1}\right) \]

       2. lower-neg.f64 N/A

          \[\leadsto -\sqrt{\frac{c}{a}} \cdot \sqrt{-1} \]

       3. sqrt-prod N/A

          \[\leadsto -\sqrt{\frac{c}{a} \cdot -1} \]

       4. lower-sqrt.f64 N/A

          \[\leadsto -\sqrt{\frac{c}{a} \cdot -1} \]

       5. *-commutative N/A

          \[\leadsto -\sqrt{-1 \cdot \frac{c}{a}} \]

       6. associate-*r/ N/A

          \[\leadsto -\sqrt{\frac{-1 \cdot c}{a}} \]

       7. mul-1-neg N/A

          \[\leadsto -\sqrt{\frac{\mathsf{neg}\left(c\right)}{a}} \]

       8. lower-/.f64 N/A

          \[\leadsto -\sqrt{\frac{\mathsf{neg}\left(c\right)}{a}} \]

       9. lower-neg.f64 37.4

          \[\leadsto -\sqrt{\frac{-c}{a}} \]

   12. Applied rewrites 37.4%

       \[\leadsto -\sqrt{\frac{-c}{a}} \]

   if 1.95000000000000007e-144 < b

   1. Initial program 71.5%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in c around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a} + \frac{c}{b}} \]
   3. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      2. lower-+.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1 \cdot \frac{b}{a}} \]

      3. lower-/.f64 N/A

         \[\leadsto \frac{c}{b} + \color{blue}{-1} \cdot \frac{b}{a} \]

      4. associate-*r/ N/A

         \[\leadsto \frac{c}{b} + \frac{-1 \cdot b}{\color{blue}{a}} \]

      5. mul-1-neg N/A

         \[\leadsto \frac{c}{b} + \frac{\mathsf{neg}\left(b\right)}{a} \]

      6. lift-neg.f64 N/A

         \[\leadsto \frac{c}{b} + \frac{-b}{a} \]

      7. lower-/.f64 80.7

         \[\leadsto \frac{c}{b} + \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 80.7%

      \[\leadsto \color{blue}{\frac{c}{b} + \frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 7: 71.8% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.2 \cdot 10^{-171}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 2.3 \cdot 10^{-144}:\\ \;\;\;\;-\sqrt{\frac{-c}{a}}\\ \mathbf{else}:\\ \;\;\;\;\frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -4.2e-171)
   (- (/ c b))
   (if (<= b 2.3e-144) (- (sqrt (/ (- c) a))) (/ (- b) a))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.2e-171) {
		tmp = -(c / b);
	} else if (b <= 2.3e-144) {
		tmp = -sqrt((-c / a));
	} else {
		tmp = -b / a;
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-4.2d-171)) then
        tmp = -(c / b)
    else if (b <= 2.3d-144) then
        tmp = -sqrt((-c / a))
    else
        tmp = -b / a
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -4.2e-171) {
		tmp = -(c / b);
	} else if (b <= 2.3e-144) {
		tmp = -Math.sqrt((-c / a));
	} else {
		tmp = -b / a;
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -4.2e-171:
		tmp = -(c / b)
	elif b <= 2.3e-144:
		tmp = -math.sqrt((-c / a))
	else:
		tmp = -b / a
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -4.2e-171)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 2.3e-144)
		tmp = Float64(-sqrt(Float64(Float64(-c) / a)));
	else
		tmp = Float64(Float64(-b) / a);
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -4.2e-171)
		tmp = -(c / b);
	elseif (b <= 2.3e-144)
		tmp = -sqrt((-c / a));
	else
		tmp = -b / a;
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -4.2e-171], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 2.3e-144], (-N[Sqrt[N[((-c) / a), $MachinePrecision]], $MachinePrecision]), N[((-b) / a), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -4.2e-171

   1. Initial program 24.7%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 77.9

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 77.9%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -4.2e-171 < b < 2.3e-144

   1. Initial program 74.8%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around inf

      \[\leadsto \color{blue}{\frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4}\right) + \frac{-1}{2} \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. distribute-lft-out N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \frac{b}{a}\right)} \]

      2. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \frac{b}{a}\right)} \]

      3. lower-+.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a}} \cdot \sqrt{-4} + \color{blue}{\frac{b}{a}}\right) \]

      4. sqrt-unprod N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      5. lower-sqrt.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      6. lower-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      7. lower-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      8. lower-/.f64 37.7

         \[\leadsto -0.5 \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{\color{blue}{a}}\right) \]

   4. Applied rewrites 37.7%

      \[\leadsto \color{blue}{-0.5 \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right)} \]
   5. Step-by-step derivation

      1. lift-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \color{blue}{\left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right)} \]

      2. lift-+.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \color{blue}{\frac{b}{a}}\right) \]

      3. lift-sqrt.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{\color{blue}{b}}{a}\right) \]

      4. lift-*.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      5. lift-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \]

      6. lift-/.f64 N/A

         \[\leadsto \frac{-1}{2} \cdot \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{\color{blue}{a}}\right) \]

      7. *-commutative N/A

         \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \color{blue}{\frac{-1}{2}} \]

      8. lower-*.f64 N/A

         \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \color{blue}{\frac{-1}{2}} \]

      9. lift-/.f64 N/A

         \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      10. lift-*.f64 N/A

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      11. lift-sqrt.f64 N/A

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      12. lift-/.f64 N/A

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \frac{-1}{2} \]

      13. lift-+.f64 37.7

          \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot -0.5 \]

   6. Applied rewrites 37.7%

      \[\leadsto \left(\sqrt{\frac{c}{a} \cdot -4} + \frac{b}{a}\right) \cdot \color{blue}{-0.5} \]

   7. Taylor expanded in a around 0

      \[\leadsto \frac{b + \sqrt{a \cdot c} \cdot \sqrt{-4}}{a} \cdot \frac{-1}{2} \]
   8. Step-by-step derivation

      1. lower-/.f64 N/A

         \[\leadsto \frac{b + \sqrt{a \cdot c} \cdot \sqrt{-4}}{a} \cdot \frac{-1}{2} \]

      2. +-commutative N/A

         \[\leadsto \frac{\sqrt{a \cdot c} \cdot \sqrt{-4} + b}{a} \cdot \frac{-1}{2} \]

      3. lower-+.f64 N/A

         \[\leadsto \frac{\sqrt{a \cdot c} \cdot \sqrt{-4} + b}{a} \cdot \frac{-1}{2} \]

      4. sqrt-unprod N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot c\right) \cdot -4} + b}{a} \cdot \frac{-1}{2} \]

      5. *-commutative N/A

         \[\leadsto \frac{\sqrt{-4 \cdot \left(a \cdot c\right)} + b}{a} \cdot \frac{-1}{2} \]

      6. associate-*r* N/A

         \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      7. *-commutative N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      8. lift-*.f64 N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      9. lift-*.f64 N/A

         \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      10. lift-sqrt.f64 74.3

          \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot -0.5 \]

      11. lift-*.f64 N/A

          \[\leadsto \frac{\sqrt{\left(a \cdot -4\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      12. *-commutative N/A

          \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot \frac{-1}{2} \]

      13. lower-*.f64 74.3

          \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot -0.5 \]

   9. Applied rewrites 74.3%

      \[\leadsto \frac{\sqrt{\left(-4 \cdot a\right) \cdot c} + b}{a} \cdot -0.5 \]

   10. Taylor expanded in a around -inf

       \[\leadsto -1 \cdot \color{blue}{\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-1}\right)} \]
   11. Step-by-step derivation

       1. mul-1-neg N/A

          \[\leadsto \mathsf{neg}\left(\sqrt{\frac{c}{a}} \cdot \sqrt{-1}\right) \]

       2. lower-neg.f64 N/A

          \[\leadsto -\sqrt{\frac{c}{a}} \cdot \sqrt{-1} \]

       3. sqrt-prod N/A

          \[\leadsto -\sqrt{\frac{c}{a} \cdot -1} \]

       4. lower-sqrt.f64 N/A

          \[\leadsto -\sqrt{\frac{c}{a} \cdot -1} \]

       5. *-commutative N/A

          \[\leadsto -\sqrt{-1 \cdot \frac{c}{a}} \]

       6. associate-*r/ N/A

          \[\leadsto -\sqrt{\frac{-1 \cdot c}{a}} \]

       7. mul-1-neg N/A

          \[\leadsto -\sqrt{\frac{\mathsf{neg}\left(c\right)}{a}} \]

       8. lower-/.f64 N/A

          \[\leadsto -\sqrt{\frac{\mathsf{neg}\left(c\right)}{a}} \]

       9. lower-neg.f64 37.4

          \[\leadsto -\sqrt{\frac{-c}{a}} \]

   12. Applied rewrites 37.4%

       \[\leadsto -\sqrt{\frac{-c}{a}} \]

   if 2.3e-144 < b

   1. Initial program 71.5%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. associate-*r/ N/A

         \[\leadsto \frac{-1 \cdot b}{\color{blue}{a}} \]

      2. mul-1-neg N/A

         \[\leadsto \frac{\mathsf{neg}\left(b\right)}{a} \]

      3. lift-neg.f64 N/A

         \[\leadsto \frac{-b}{a} \]

      4. lower-/.f64 80.2

         \[\leadsto \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 80.2%

      \[\leadsto \color{blue}{\frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 8: 70.9% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -1.15 \cdot 10^{-70}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{elif}\;b \leq 3.1 \cdot 10^{-129}:\\ \;\;\;\;\sqrt{\frac{-c}{a}}\\ \mathbf{else}:\\ \;\;\;\;\frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -1.15e-70)
   (- (/ c b))
   (if (<= b 3.1e-129) (sqrt (/ (- c) a)) (/ (- b) a))))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -1.15e-70) {
		tmp = -(c / b);
	} else if (b <= 3.1e-129) {
		tmp = sqrt((-c / a));
	} else {
		tmp = -b / a;
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-1.15d-70)) then
        tmp = -(c / b)
    else if (b <= 3.1d-129) then
        tmp = sqrt((-c / a))
    else
        tmp = -b / a
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -1.15e-70) {
		tmp = -(c / b);
	} else if (b <= 3.1e-129) {
		tmp = Math.sqrt((-c / a));
	} else {
		tmp = -b / a;
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -1.15e-70:
		tmp = -(c / b)
	elif b <= 3.1e-129:
		tmp = math.sqrt((-c / a))
	else:
		tmp = -b / a
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -1.15e-70)
		tmp = Float64(-Float64(c / b));
	elseif (b <= 3.1e-129)
		tmp = sqrt(Float64(Float64(-c) / a));
	else
		tmp = Float64(Float64(-b) / a);
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -1.15e-70)
		tmp = -(c / b);
	elseif (b <= 3.1e-129)
		tmp = sqrt((-c / a));
	else
		tmp = -b / a;
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -1.15e-70], (-N[(c / b), $MachinePrecision]), If[LessEqual[b, 3.1e-129], N[Sqrt[N[((-c) / a), $MachinePrecision]], $MachinePrecision], N[((-b) / a), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if b < -1.15e-70

   1. Initial program 17.8%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 85.6

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 85.6%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -1.15e-70 < b < 3.1e-129

   1. Initial program 72.0%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around -inf

      \[\leadsto \color{blue}{\sqrt{\frac{c}{a}} \cdot \sqrt{-1}} \]
   3. Step-by-step derivation

      1. sqrt-unprod N/A

         \[\leadsto \sqrt{\frac{c}{a} \cdot -1} \]

      2. lower-sqrt.f64 N/A

         \[\leadsto \sqrt{\frac{c}{a} \cdot -1} \]

      3. lower-*.f64 N/A

         \[\leadsto \sqrt{\frac{c}{a} \cdot -1} \]

      4. lower-/.f64 32.8

         \[\leadsto \sqrt{\frac{c}{a} \cdot -1} \]

   4. Applied rewrites 32.8%

      \[\leadsto \color{blue}{\sqrt{\frac{c}{a} \cdot -1}} \]
   5. Step-by-step derivation

      1. count-2-rev 32.8

         \[\leadsto \sqrt{\frac{c}{a} \cdot \color{blue}{-1}} \]

      2. lift-*.f64 N/A

         \[\leadsto \sqrt{\frac{c}{a} \cdot -1} \]

      3. lift-/.f64 N/A

         \[\leadsto \sqrt{\frac{c}{a} \cdot -1} \]

      4. *-commutative N/A

         \[\leadsto \sqrt{-1 \cdot \frac{c}{a}} \]

      5. associate-*r/ N/A

         \[\leadsto \sqrt{\frac{-1 \cdot c}{a}} \]

      6. mul-1-neg N/A

         \[\leadsto \sqrt{\frac{\mathsf{neg}\left(c\right)}{a}} \]

      7. lower-/.f64 N/A

         \[\leadsto \sqrt{\frac{\mathsf{neg}\left(c\right)}{a}} \]

      8. lower-neg.f64 32.8

         \[\leadsto \sqrt{\frac{-c}{a}} \]

   6. Applied rewrites 32.8%

      \[\leadsto \color{blue}{\sqrt{\frac{-c}{a}}} \]

   if 3.1e-129 < b

   1. Initial program 71.1%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. associate-*r/ N/A

         \[\leadsto \frac{-1 \cdot b}{\color{blue}{a}} \]

      2. mul-1-neg N/A

         \[\leadsto \frac{\mathsf{neg}\left(b\right)}{a} \]

      3. lift-neg.f64 N/A

         \[\leadsto \frac{-b}{a} \]

      4. lower-/.f64 81.6

         \[\leadsto \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 81.6%

      \[\leadsto \color{blue}{\frac{-b}{a}} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 9: 67.3% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -2 \cdot 10^{-310}:\\ \;\;\;\;-\frac{c}{b}\\ \mathbf{else}:\\ \;\;\;\;\frac{-b}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (if (<= b -2e-310) (- (/ c b)) (/ (- b) a)))

C

double code(double a, double b, double c) {
	double tmp;
	if (b <= -2e-310) {
		tmp = -(c / b);
	} else {
		tmp = -b / a;
	}
	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(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8) :: tmp
    if (b <= (-2d-310)) then
        tmp = -(c / b)
    else
        tmp = -b / a
    end if
    code = tmp
end function

Java

public static double code(double a, double b, double c) {
	double tmp;
	if (b <= -2e-310) {
		tmp = -(c / b);
	} else {
		tmp = -b / a;
	}
	return tmp;
}

Python

def code(a, b, c):
	tmp = 0
	if b <= -2e-310:
		tmp = -(c / b)
	else:
		tmp = -b / a
	return tmp

Julia

function code(a, b, c)
	tmp = 0.0
	if (b <= -2e-310)
		tmp = Float64(-Float64(c / b));
	else
		tmp = Float64(Float64(-b) / a);
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b, c)
	tmp = 0.0;
	if (b <= -2e-310)
		tmp = -(c / b);
	else
		tmp = -b / a;
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_, c_] := If[LessEqual[b, -2e-310], (-N[(c / b), $MachinePrecision]), N[((-b) / a), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < -1.999999999999994e-310

   1. Initial program 32.2%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in b around -inf

      \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
   3. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

      2. lower-neg.f64 N/A

         \[\leadsto -\frac{c}{b} \]

      3. lower-/.f64 67.0

         \[\leadsto -\frac{c}{b} \]

   4. Applied rewrites 67.0%

      \[\leadsto \color{blue}{-\frac{c}{b}} \]

   if -1.999999999999994e-310 < b

   1. Initial program 72.7%

      \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

   2. Taylor expanded in a around 0

      \[\leadsto \color{blue}{-1 \cdot \frac{b}{a}} \]
   3. Step-by-step derivation

      1. associate-*r/ N/A

         \[\leadsto \frac{-1 \cdot b}{\color{blue}{a}} \]

      2. mul-1-neg N/A

         \[\leadsto \frac{\mathsf{neg}\left(b\right)}{a} \]

      3. lift-neg.f64 N/A

         \[\leadsto \frac{-b}{a} \]

      4. lower-/.f64 67.5

         \[\leadsto \frac{-b}{\color{blue}{a}} \]

   4. Applied rewrites 67.5%

      \[\leadsto \color{blue}{\frac{-b}{a}} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 10: 34.6% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ -\frac{c}{b} \end{array} \]

FPCore

(FPCore (a b c) :precision binary64 (- (/ c b)))

C

double code(double a, double b, double c) {
	return -(c / b);
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(a, b, c)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    code = -(c / b)
end function

Java

public static double code(double a, double b, double c) {
	return -(c / b);
}

Python

def code(a, b, c):
	return -(c / b)

Julia

function code(a, b, c)
	return Float64(-Float64(c / b))
end

MATLAB

function tmp = code(a, b, c)
	tmp = -(c / b);
end

Wolfram

code[a_, b_, c_] := (-N[(c / b), $MachinePrecision])

Derivation

1. Initial program 52.5%

   \[\frac{\left(-b\right) - \sqrt{b \cdot b - 4 \cdot \left(a \cdot c\right)}}{2 \cdot a} \]

2. Taylor expanded in b around -inf

   \[\leadsto \color{blue}{-1 \cdot \frac{c}{b}} \]
3. Step-by-step derivation

   1. mul-1-neg N/A

      \[\leadsto \mathsf{neg}\left(\frac{c}{b}\right) \]

   2. lower-neg.f64 N/A

      \[\leadsto -\frac{c}{b} \]

   3. lower-/.f64 34.6

      \[\leadsto -\frac{c}{b} \]

4. Applied rewrites 34.6%

   \[\leadsto \color{blue}{-\frac{c}{b}} \]
5. Add Preprocessing

Developer Target 1: 99.7% accurate, 0.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left|\frac{b}{2}\right|\\ t_1 := \sqrt{\left|a\right|} \cdot \sqrt{\left|c\right|}\\ t_2 := \begin{array}{l} \mathbf{if}\;\mathsf{copysign}\left(a, c\right) = a:\\ \;\;\;\;\sqrt{t\_0 - t\_1} \cdot \sqrt{t\_0 + t\_1}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{hypot}\left(\frac{b}{2}, t\_1\right)\\ \end{array}\\ \mathbf{if}\;b < 0:\\ \;\;\;\;\frac{c}{t\_2 - \frac{b}{2}}\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{b}{2} + t\_2}{-a}\\ \end{array} \end{array} \]

FPCore

(FPCore (a b c)
 :precision binary64
 (let* ((t_0 (fabs (/ b 2.0)))
        (t_1 (* (sqrt (fabs a)) (sqrt (fabs c))))
        (t_2
         (if (== (copysign a c) a)
           (* (sqrt (- t_0 t_1)) (sqrt (+ t_0 t_1)))
           (hypot (/ b 2.0) t_1))))
   (if (< b 0.0) (/ c (- t_2 (/ b 2.0))) (/ (+ (/ b 2.0) t_2) (- a)))))

C

double code(double a, double b, double c) {
	double t_0 = fabs((b / 2.0));
	double t_1 = sqrt(fabs(a)) * sqrt(fabs(c));
	double tmp;
	if (copysign(a, c) == a) {
		tmp = sqrt((t_0 - t_1)) * sqrt((t_0 + t_1));
	} else {
		tmp = hypot((b / 2.0), t_1);
	}
	double t_2 = tmp;
	double tmp_1;
	if (b < 0.0) {
		tmp_1 = c / (t_2 - (b / 2.0));
	} else {
		tmp_1 = ((b / 2.0) + t_2) / -a;
	}
	return tmp_1;
}

Java

public static double code(double a, double b, double c) {
	double t_0 = Math.abs((b / 2.0));
	double t_1 = Math.sqrt(Math.abs(a)) * Math.sqrt(Math.abs(c));
	double tmp;
	if (Math.copySign(a, c) == a) {
		tmp = Math.sqrt((t_0 - t_1)) * Math.sqrt((t_0 + t_1));
	} else {
		tmp = Math.hypot((b / 2.0), t_1);
	}
	double t_2 = tmp;
	double tmp_1;
	if (b < 0.0) {
		tmp_1 = c / (t_2 - (b / 2.0));
	} else {
		tmp_1 = ((b / 2.0) + t_2) / -a;
	}
	return tmp_1;
}

Python

def code(a, b, c):
	t_0 = math.fabs((b / 2.0))
	t_1 = math.sqrt(math.fabs(a)) * math.sqrt(math.fabs(c))
	tmp = 0
	if math.copysign(a, c) == a:
		tmp = math.sqrt((t_0 - t_1)) * math.sqrt((t_0 + t_1))
	else:
		tmp = math.hypot((b / 2.0), t_1)
	t_2 = tmp
	tmp_1 = 0
	if b < 0.0:
		tmp_1 = c / (t_2 - (b / 2.0))
	else:
		tmp_1 = ((b / 2.0) + t_2) / -a
	return tmp_1

Julia

function code(a, b, c)
	t_0 = abs(Float64(b / 2.0))
	t_1 = Float64(sqrt(abs(a)) * sqrt(abs(c)))
	tmp = 0.0
	if (copysign(a, c) == a)
		tmp = Float64(sqrt(Float64(t_0 - t_1)) * sqrt(Float64(t_0 + t_1)));
	else
		tmp = hypot(Float64(b / 2.0), t_1);
	end
	t_2 = tmp
	tmp_1 = 0.0
	if (b < 0.0)
		tmp_1 = Float64(c / Float64(t_2 - Float64(b / 2.0)));
	else
		tmp_1 = Float64(Float64(Float64(b / 2.0) + t_2) / Float64(-a));
	end
	return tmp_1
end

MATLAB

function tmp_3 = code(a, b, c)
	t_0 = abs((b / 2.0));
	t_1 = sqrt(abs(a)) * sqrt(abs(c));
	tmp = 0.0;
	if ((sign(c) * abs(a)) == a)
		tmp = sqrt((t_0 - t_1)) * sqrt((t_0 + t_1));
	else
		tmp = hypot((b / 2.0), t_1);
	end
	t_2 = tmp;
	tmp_2 = 0.0;
	if (b < 0.0)
		tmp_2 = c / (t_2 - (b / 2.0));
	else
		tmp_2 = ((b / 2.0) + t_2) / -a;
	end
	tmp_3 = tmp_2;
end

Wolfram

code[a_, b_, c_] := Block[{t$95$0 = N[Abs[N[(b / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Sqrt[N[Abs[a], $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Abs[c], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = If[Equal[N[With[{TMP1 = Abs[a], TMP2 = Sign[c]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision], a], N[(N[Sqrt[N[(t$95$0 - t$95$1), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[Sqrt[N[(b / 2.0), $MachinePrecision] ^ 2 + t$95$1 ^ 2], $MachinePrecision]]}, If[Less[b, 0.0], N[(c / N[(t$95$2 - N[(b / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b / 2.0), $MachinePrecision] + t$95$2), $MachinePrecision] / (-a)), $MachinePrecision]]]]]

Reproduce

herbie shell --seed 2025110 
(FPCore (a b c)
  :name "quadm (p42, negative)"
  :precision binary64
  :herbie-expected 10

  :alt
  (! :herbie-platform c (let ((sqtD (let ((x (* (sqrt (fabs a)) (sqrt (fabs c))))) (if (== (copysign a c) a) (* (sqrt (- (fabs (/ b 2)) x)) (sqrt (+ (fabs (/ b 2)) x))) (hypot (/ b 2) x))))) (if (< b 0) (/ c (- sqtD (/ b 2))) (/ (+ (/ b 2) sqtD) (- a)))))

  (/ (- (- b) (sqrt (- (* b b) (* 4.0 (* a c))))) (* 2.0 a)))