Unlike the int
type, which is typically represented as a two's complement number, a float
is a floating point type, which means it stores values using a mantissa and an exponent. This means that the typical wrapping behavior seen with signed integer types doesn't apply to floating point types.
In the case of 2,500,000,000, this will actually get stored as 0x1.2A05F2 x 231.
Floating point types are typically stored using IEEE 754 floating point format. In the case of a single precision floating point (which a float
typically is), it has 1 sign bit, 8 exponent bits, and 24 mantissa bits (with 23 bits stored, as the high order "1" bit is implied).
While this format can't "wrap" from positive to negative, it is subject to 2 things:
- Loss of precision
- Overflow of the exponent
As an example of precision loss, let's use a decimal floating point format with a 3 digit mantissa and a 2 digit exponent. If we multiply 2.34 x 1010 by 6.78 x 1010, you get 1.58652 x 1021, but because of the 3 digit precision it gets truncated to 1.58 x 1021. So we lose the least significant digits.
To illustrate exponent overflow, suppose we were to multiply 2.00 x 1060 by 3.00 x 1050. You'd get 6.00 x 10110. But because the maximum value of an exponent is 99, this is an overflow. IEEE 754 has a special notation for infinity which it uses in the case of overflow where it sets the mantissa to all 0 bits and the exponent to all 1 bits, and the sign bit can be used to distinguish positive infinity and negative infinity.