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fconst_2 0d 0000 1101 → 2.0f push 2.0f on the stack fdiv 6e 0110 1110 value1, value2 → result divide two floats fload 17 0001 0111 1: index → value load a float value from a local variable #index: fload_0 22 0010 0010 → value load a float value from local variable 0 fload_1 23 0010 0011 → value load a float value from local variable 1 ...
Data conversion is the conversion of computer data from one format to another. Throughout a computer environment, data is encoded in a variety of ways. For example, computer hardware is built on the basis of certain standards, which requires that data contains, for example, parity bit checks.
Some programming languages (or compilers for them) provide a built-in (primitive) or library decimal data type to represent non-repeating decimal fractions like 0.3 and −1.17 without rounding, and to do arithmetic on them. Examples are the decimal.Decimal or num7.Num type of Python, and analogous types provided by other languages.
If errors in representation and computation are more important than the speed of conversion to and from display, a scaled binary representation may be used, which stores a decimal number as a binary-encoded integer and a binary-encoded signed decimal exponent. For example, 0.2 can be represented as 2 × 10 −1.
Dot-decimal notation is a presentation format for numerical data. It consists of a string of decimal numbers, using the full stop (dot) as a separation character. [1]A common use of dot-decimal notation is in information technology where it is a method of writing numbers in octet-grouped base-10 numbers. [2]
For example, an input box accepting numeric data may reject the letter 'O'. File existence check Checks that a file with a specified name exists. This check is essential for programs that use file handling. Format check Checks that the data is in a specified format (template), e.g., dates have to be in the format YYYY-MM-DD.
For example, while a fixed-point representation that allocates 8 decimal digits and 2 decimal places can represent the numbers 123456.78, 8765.43, 123.00, and so on, a floating-point representation with 8 decimal digits could also represent 1.2345678, 1234567.8, 0.000012345678, 12345678000000000, and so on.
Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point.