Average Error: 38.8 → 0.0
Time: 1.6s
Precision: 64
\[\left(x + 1\right) \cdot \left(x + 1\right) - 1\]
↓
\[x \cdot 2 + {x}^{2}\]
\left(x + 1\right) \cdot \left(x + 1\right) - 1
↓
x \cdot 2 + {x}^{2}
double code(double x) {
	return ((double) (((double) (((double) (x + 1.0)) * ((double) (x + 1.0)))) - 1.0));
}
↓
double code(double x) {
	return ((double) (((double) (x * 2.0)) + ((double) pow(x, 2.0))));
}

Error

Bits error versus x

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Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 38.8

    \[\left(x + 1\right) \cdot \left(x + 1\right) - 1\]

  2. Taylor expanded around 0 0.0

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

  3. Simplified0.0

    \[\leadsto \color{blue}{x \cdot \left(2 + x\right)}\]
  4. Using strategy rm

  5. Applied distribute-lft-in0.0

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

  6. Simplified0.0

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

  7. Final simplification0.0

    \[\leadsto x \cdot 2 + {x}^{2}\]

Reproduce

herbie shell --seed 2020126 
(FPCore (x)
  :name "Expanding a square"
  :precision binary64
  (- (* (+ x 1.0) (+ x 1.0)) 1.0))