Can modifying PHP's precision setting guarantee accurate 2-digit decimal calculations?

Precision Workaround for Floating Point Issue

Floating-point computations can lead to discrepancies due to the limitations of binary representation. While one potential remedy is to alter the precision setting in php.ini, it's crucial to assess its reliability.

Suitability for 2-Digit Decimal Precision

No, modifying the precision setting alone cannot guarantee precise 2-digit calculations, particularly when dealing with quantities greater than 10^6.

Example of Failure

To demonstrate the shortcomings of this approach, consider the following example:

$a = 5.88;
$q = 2.49;
$b = $a * 0.01;
echo ($a * $q) - $b;

Output:

14.5824

Even with a precision of 8, the result is not a precise 2-digit value due to intermediate calculations.

Alternative Approaches

Instead of relying on precision workarounds, consider alternative solutions:

• Use bcmath for accurate decimal calculations.
• Utilize number_format for consistent 2-digit rounding.
• Multiply values by 100 to work with integers and then divide by 100 for the final result, ensuring accuracy.

Update

Question 1: Failure Range with Precision = 8

It's impractical to test for all combinations of numbers between 0 and 999999.99. However, a simple test demonstrates that even with a precision of 8, inaccuracies can occur:

$a = 0.19;
$b = 0.16;
$i = 0;
for ($c = 0.01; $c <= 0.07; $c += 0.01) {
    $i = $i + $c;
}
echo $i - ($a + $b);

Output:

0.000055879354492188

This error is due to the accumulation of rounding errors during the addition of floating-point numbers.

Question 2: Mathematical Estimation of Failure Threshold

Estimating the failure threshold requires complex mathematical analysis. A comprehensive discussion on the topic is beyond the scope of this article.

However, it's important to remember that floating-point calculations have inherent accuracy limitations due to the binary representation of numbers. Therefore, relying on precision workarounds alone is not a foolproof solution.

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