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In C++, associative containers are a group of class templates in the standard library of the C++ programming language that implement ordered associative arrays. [1] Being templates , they can be used to store arbitrary elements, such as integers or custom classes.
Another 3rd-party library, uthash, also creates associative arrays from C structures. A structure represents a value, and one of the structure fields serves as the key. [2] Finally, the GLib library also supports associative arrays, along with many other advanced data types and is the recommended implementation of the GNU Project. [3]
Structure of arrays (SoA) is a layout separating elements of a record (or 'struct' in the C programming language) into one parallel array per field. [1] The motivation is easier manipulation with packed SIMD instructions in most instruction set architectures, since a single SIMD register can load homogeneous data, possibly transferred by a wide internal datapath (e.g. 128-bit).
Bit field – Data structure that maps one or more adjacent bits; Flexible array member – C language feature in which a struct may contain as its last member an array with no specified size; Passive data structure – Another term for record; Union type – Data type that allows for values that are one of multiple different data types
In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.
Off-side rule languages: Boo, Cobra, CoffeeScript, F#, Haskell (in do-notation when braces are omitted), LiveScript, occam, Python, Nemerle (Optional; the user may use white-space sensitive syntax instead of the curly-brace syntax if they so desire), Nim, Scala (Optional, as in Nemerle)
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 ...
Arrays are useful mostly because the element indices can be computed at run time. Among other things, this feature allows a single iterative statement to process arbitrarily many elements of an array. For that reason, the elements of an array data structure are required to have the same size and should use the same data representation.