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Conversely, precision can be lost when converting representations from integer to floating-point, since a floating-point type may be unable to exactly represent all possible values of some integer type. For example, float might be an IEEE 754 single precision type, which cannot represent the integer 16777217 exactly, while a 32-bit integer type ...
Many languages have explicit pointers or references. Reference types differ from these in that the entities they refer to are always accessed via references; for example, whereas in C++ it's possible to have either a std:: string and a std:: string *, where the former is a mutable string and the latter is an explicit pointer to a mutable string (unless it's a null pointer), in Java it is only ...
Whether it is a console or a graphical interface application, the program must have an entry point of some sort. The entry point of a C# application is the Main method. There can only be one declaration of this method, and it is a static method in a class. It usually returns void and is passed command-line arguments as an array of strings.
A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...
Complex number in C99, Fortran, Common Lisp, Python, D, Go. This is two floating-point numbers, a real part and an imaginary part. Rational number in Common Lisp; Arbitrary-precision Integer type in Common Lisp, Erlang, Haskell; Associative arrays, records or sets in Perl, PHP, Python, Ruby, JavaScript, Lua, D, Go
However, on modern standard computers (i.e., implementing IEEE 754), one may safely assume that the endianness is the same for floating-point numbers as for integers, making the conversion straightforward regardless of data type. Small embedded systems using special floating-point formats may be another matter, however.
Intersection types are useful for describing overloaded function types: for example, if "int → int" is the type of functions taking an integer argument and returning an integer, and "float → float" is the type of functions taking a float argument and returning a float, then the intersection of these two types can be used to describe ...
An array data structure can be mathematically modeled as an abstract data structure (an abstract array) with two operations get(A, I): the data stored in the element of the array A whose indices are the integer tuple I. set(A, I, V): the array that results by setting the value of that element to V. These operations are required to satisfy the ...