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In computer programming, the Schwartzian transform is a technique used to improve the efficiency of sorting a list of items. This idiom [1] is appropriate for comparison-based sorting when the ordering is actually based on the ordering of a certain property (the key) of the elements, where computing that property is an intensive operation that should be performed a minimal number of times.
In Java associative arrays are implemented as "maps", which are part of the Java collections framework. Since J2SE 5.0 and the introduction of generics into Java, collections can have a type specified; for example, an associative array that maps strings to strings might be specified as follows:
A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored. A map implemented by a hash table is called a hash map.
The "QMap" key/value dictionary (up to Qt 4) template class of Qt is implemented with skip lists. [13] Redis, an ANSI-C open-source persistent key/value store for Posix systems, uses skip lists in its implementation of ordered sets. [14] Discord uses skip lists to handle storing and updating the list of members in a server. [15]
In an associative array, the association between a key and a value is often known as a "mapping"; the same word may also be used to refer to the process of creating a new association. The operations that are usually defined for an associative array are: [3] [4] [8] Insert or put
The shuffle sort [6] is a variant of bucket sort that begins by removing the first 1/8 of the n items to be sorted, sorts them recursively, and puts them in an array. This creates n /8 "buckets" to which the remaining 7/8 of the items are distributed.
Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...
Sorted arrays are the most space-efficient data structure with the best locality of reference for sequentially stored data. [citation needed]Elements within a sorted array are found using a binary search, in O(log n); thus sorted arrays are suited for cases when one needs to be able to look up elements quickly, e.g. as a set or multiset data structure.