Overview

A floating-point data type uses a formulaic representation of real numbers as an approximation so as to support a trade-off between range and precision. For this reason, floating-point computation is often found in systems which include very small and very large real numbers, which require fast processing times. A number is, in general, represented approximately to a fixed number of significant digits and scaled using an exponent in some fixed base.^[1]

Discussion

The floating-point data type is a family of data types that act alike and differ only in the size of their domains (the allowable values). The floating-point family of data types represents number values with fractional parts. They are technically stored as two integer values: a mantissa and an exponent. The floating-point family has the same attributes and acts or behaves similarly in all programming languages. They can always store negative or positive values thus they always are signed; unlike the integer data type that could be unsigned. The domain for floating-point data types varies because they could represent very large numbers or very small numbers. Rather than talk about the actual values, we mention the precision. The more bytes of storage the larger the mantissa and exponent, thus more precision.

Key Terms

double

The most often used floating-point family data type used.

mantissa exponent

The two integer parts of a floating-point value.

precision

The effect on the domain of floating-point values given a larger or smaller storage area in bytes.

References

• cnx.org: Programming Fundamentals – A Modular Structured Approach using C++