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The "decimal" data type of the C# and Python programming languages, and the decimal formats of the IEEE 754-2008 standard, are designed to avoid the problems of binary floating-point representations when applied to human-entered exact decimal values, and make the arithmetic always behave as expected when numbers are printed in decimal.
C# has a built-in data type decimal consisting of 128 bits resulting in 28–29 significant digits. It has an approximate range of ±1.0 × 10 −28 to ±7.9228 × 10 28. [1] Starting with Python 2.4, Python's standard library includes a Decimal class in the module decimal. [2] Ruby's standard library includes a BigDecimal class in the module ...
In C#, apart from the distinction between value types and reference types, there is also a separate concept called reference variables. [3] A reference variable, once declared and bound, behaves as an alias of the original variable, but it can also be rebounded to another variable by using the reference assignment operator = ref .
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.
8 bits Byte, octet, minimum size of char in C99( see limits.h CHAR_BIT) −128 to +127 0 to 255 2 bytes 16 bits x86 word, minimum size of short and int in C −32,768 to +32,767 0 to 65,535 4 bytes 32 bits x86 double word, minimum size of long in C, actual size of int for most modern C compilers, [8] pointer for IA-32-compatible processors
Single precision is termed REAL in Fortran; [1] SINGLE-FLOAT in Common Lisp; [2] float in C, C++, C# and Java; [3] Float in Haskell [4] and Swift; [5] and Single in Object Pascal , Visual Basic, and MATLAB. However, float in Python, Ruby, PHP, and OCaml and single in versions of Octave before 3.2 refer to double-precision numbers.
In decimal interchange formats they require no special encoding because the format supports unnormalized numbers directly. Mathematically speaking, the normalized floating-point numbers of a given sign are roughly logarithmically spaced, and as such any finite-sized normal float cannot include zero. The subnormal floats are a linearly spaced ...
[5] [6] Another is in situations where artificial limits and overflows would be inappropriate. It is also useful for checking the results of fixed-precision calculations, and for determining optimal or near-optimal values for coefficients needed in formulae, for example the 1 3 {\textstyle {\sqrt {\frac {1}{3}}}} that appears in Gaussian ...