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For example, to perform an element by element sum of two arrays, a and b to produce a third c, it is only necessary to write c = a + b 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)
Two generalizations of assoc exist: assoc-if expects a predicate function that tests each entry's key, returning the first entry for which the predicate produces a non-NIL value upon invocation. assoc-if-not inverts the logic, accepting the same arguments, but returning the first entry generating NIL.
A difference list f is a single-argument function append L, which when given a linked list X as argument, returns a linked list containing L prepended to X. Concatenation of difference lists is implemented as function composition. The contents may be retrieved using f []. [1]
The literature on programming languages contains an abundance of informal claims about their relative expressive power, but there is no framework for formalizing such statements nor for deriving interesting consequences. [52] This table provides two measures of expressiveness from two different sources.
A singly-linked list structure, implementing a list with three integer elements. The term list is also used for several concrete data structures that can be used to implement abstract lists, especially linked lists and arrays. In some contexts, such as in Lisp programming, the term list may refer specifically to a linked list rather than an array.
In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert' operations. The dictionary problem is the classic problem of designing efficient data structures that implement associative arrays. [2] The two major solutions to the dictionary problem are hash tables and search trees.
This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.
Function rank is an important concept to array programming languages in general, by analogy to tensor rank in mathematics: functions that operate on data may be classified by the number of dimensions they act on. Ordinary multiplication, for example, is a scalar ranked function because it operates on zero-dimensional data (individual numbers).