Concept
Array (data structure)
Related concepts (44)
Zero-based numbering
Zero-based numbering is a way of numbering in which the initial element of a sequence is assigned the index 0, rather than the index 1 as is typical in everyday non-mathematical or non-programming circumstances. Under zero-based numbering, the initial element is sometimes termed the zeroth element, rather than the first element; zeroth is a coined ordinal number corresponding to the number zero. In some cases, an object or value that does not (originally) belong to a given sequence, but which could be naturally placed before its initial element, may be termed the zeroth element.
Aliasing (computing)
In computing, aliasing describes a situation in which a data location in memory can be accessed through different symbolic names in the program. Thus, modifying the data through one name implicitly modifies the values associated with all aliased names, which may not be expected by the programmer. As a result, aliasing makes it particularly difficult to understand, analyze and optimize programs. Aliasing analysers intend to make and compute useful information for understanding aliasing in programs.
Linear probing
Linear probing is a scheme in computer programming for resolving collisions in hash tables, data structures for maintaining a collection of key–value pairs and looking up the value associated with a given key. It was invented in 1954 by Gene Amdahl, Elaine M. McGraw, and Arthur Samuel and first analyzed in 1963 by Donald Knuth. Along with quadratic probing and double hashing, linear probing is a form of open addressing. In these schemes, each cell of a hash table stores a single key–value pair.
Perfect hash function
In computer science, a perfect hash function h for a set S is a hash function that maps distinct elements in S to a set of m integers, with no collisions. In mathematical terms, it is an injective function. Perfect hash functions may be used to implement a lookup table with constant worst-case access time. A perfect hash function can, as any hash function, be used to implement hash tables, with the advantage that no collision resolution has to be implemented.
String-searching algorithm
In computer science, string-searching algorithms, sometimes called string-matching algorithms, are an important class of string algorithms that try to find a place where one or several strings (also called patterns) are found within a larger string or text. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet (finite set) Σ. Σ may be a human language alphabet, for example, the letters A through Z and other applications may use a binary alphabet (Σ = {0,1}) or a DNA alphabet (Σ = {A,C,G,T}) in bioinformatics.
Offset (computer science)
In computer science, an offset within an array or other data structure object is an integer indicating the distance (displacement) between the beginning of the object and a given element or point, presumably within the same object. The concept of a distance is valid only if all elements of the object are of the same size (typically given in bytes or words). For example, if A is an array of characters containing "abcdef", the fourth element containing the character 'd' has an offset of three from the start of A.
Dope vector
In computer programming, a dope vector is a data structure used to hold information about a data object, especially its memory layout. Dope vectors are most commonly used to describe arrays, which commonly store multiple instances of a particular datatype as a contiguous block of memory. For example, an array containing 100 elements, each of which occupies 32 bytes, requires 100 × 32 bytes. By itself, such a memory block has no place to keep track of how large the array (or other object) is overall, how large each element within it is, or how many elements it contains.
Implicit data structure
In computer science, an implicit data structure or space-efficient data structure is a data structure that stores very little information other than the main or required data: a data structure that requires low overhead. They are called "implicit" because the position of the elements carries meaning and relationship between elements; this is contrasted with the use of pointers to give an explicit relationship between elements. Definitions of "low overhead" vary, but generally means constant overhead; in big O notation, O(1) overhead.
Index register
An index register in a computer's CPU is a processor register (or an assigned memory location) used for pointing to operand addresses during the run of a program. It is useful for stepping through strings and arrays. It can also be used for holding loop iterations and counters. In some architectures it is used for read/writing blocks of memory. Depending on the architecture it maybe a dedicated index register or a general-purpose register.
Judy array
In computer science, a Judy array is a data structure implementing a type of associative array with high performance and low memory usage. Unlike most other key-value stores, Judy arrays use no hashing, leverage compression on their keys (which may be integers or strings), and can efficiently represent sparse data; that is, they may have large ranges of unassigned indices without greatly increasing memory usage or processing time. They are designed to remain efficient even on structures with sizes in the peta-element range, with performance scaling on the order of O(log n).