Which statement best describes floating-point arithmetic?

• A. It uses a fixed-point representation where the decimal point is at a fixed position.
• B. It represents numbers as a significand multiplied by a base raised to an integer exponent.
• C. It stores numbers as character strings.
• D. It uses only integers for storage.

Answer: (B)

Floating-point arithmetic encodes numbers as a significand (mantissa) multiplied by a base raised to an integer exponent. In most systems the base is 2, so numbers are stored as something like a mantissa times 2 to the power of an exponent. This structure lets computers represent a huge range of magnitudes with a fixed number of bits by adjusting the exponent, effectively moving the position of the decimal (or binary) point.

This approach is different from fixed-point representation, where the decimal point stays at a fixed place and cannot adapt to very large or very small values. It’s also not how numbers are stored as plain text strings, nor is it limited to integers. Because the mantissa has finite precision, some real numbers can only be approximated, leading to rounding errors or small representation gaps.