# Handling of floating point rounding errors.

2008-01-27*In this article we demonstrate that a very elementary mathematical statement can raise big concerns for numerical applications.*

## Reasoning

Try this simple yet tricky code:

System.out.println(0.1 + 0.1 + 0.1);

Oh well... the result is: 0.30000000000000004

What??? So... 0.1 + 0.1 + 0.1 is not 0.3 ???

## Problem

This problem arises the way floating point numbers are represented in the processor and how they participate in floating point calculations.

Notice that the comparison `if (x==0.3)`

jumped to the else branch. After the sum, the result was `0.30000000000000004`

and not `0.3`

as we expected. The behaviour of the if statement is correct. In fact, the error is located between the keyboard and the chair: you simply cannot do such comparison!

You have to:

- remember that floating point errors may happen;
- evaluate the epsilon associated to the operations you previously done;
- you have to consider a certain range in your comparisions

like this:

epsilon = blah blah blah; // calculate epsilon somehow if ((x>=0.3-epsilon) && (x<=0.3+epsilon)) ...

## Solution

JQuantLib takes the same approach as QuantLib. It calculates epsilon after a sequence of mathematical operations which gives us the order of magnitude of the error.

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