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Purely Functional Data Structure
In computer science, a purely functional data structure is a data structure that can be directly implemented in a purely functional language. The main difference between an arbitrary data structure and a purely functional one is that the latter is (strongly) immutable. This restriction ensures the data structure possesses the advantages of immutable objects: (full) persistency, quick copy of objects, and thread safety. Efficient purely functional data structures may require the use of lazy evaluation and memoization. Definition Persistent data structures have the property of keeping previous versions of themselves unmodified. On the other hand, non-persistent structures such as arrays admit a destructive update,
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Computer Science
Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, applied disciplines (including the design and implementation of Computer architecture, hardware and Software engineering, software). Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and preventing security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of re ...
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Balanced Tree
In computer science, a self-balancing binary search tree (BST) is any node-based binary search tree that automatically keeps its height (maximal number of levels below the root) small in the face of arbitrary item insertions and deletions.Donald Knuth. ''The Art of Computer Programming'', Volume 3: ''Sorting and Searching'', Second Edition. Addison-Wesley, 1998. . Section 6.2.3: Balanced Trees, pp.458–481. These operations when designed for a self-balancing binary search tree, contain precautionary measures against boundlessly increasing tree height, so that these abstract data structures receive the attribute "self-balancing". For height-balanced binary trees, the height is defined to be logarithmic O(\log n) in the number n of items. This is the case for many binary search trees, such as AVL trees and red–black trees. Splay trees and treaps are self-balancing but not height-balanced, as their height is not guaranteed to be logarithmic in the number of items. Self-balancin ...
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Priority Queue
In computer science, a priority queue is an abstract data type similar to a regular queue (abstract data type), queue or stack (abstract data type), stack abstract data type. In a priority queue, each element has an associated ''priority'', which determines its order of service. Priority queue serves highest priority items first. Priority values have to be instances of an ordered data type, and higher priority can be given either to the lesser or to the greater values with respect to the given order relation. For example, in Java (programming language), Java standard library, ''PriorityQueues the least elements with respect to the order have the highest priority. This implementation detail is without much practical significance, since passing to the converse relation, opposite order relation turns the least values into the greatest, and vice versa. While priority queues are often implemented using Heap (data structure) , heaps, they are conceptually distinct. A priority queue can ...
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Search Tree
In computer science, a search tree is a tree data structure used for locating specific keys from within a set. In order for a tree to function as a search tree, the key for each node must be greater than any keys in subtrees on the left, and less than any keys in subtrees on the right. The advantage of search trees is their efficient search time given the tree is reasonably balanced, which is to say the leaves at either end are of comparable depths. Various search-tree data structures exist, several of which also allow efficient insertion and deletion of elements, which operations then have to maintain tree balance. Search trees are often used to implement an associative array. The search tree algorithm uses the key from the key–value pair to find a location, and then the application stores the entire key–value pair at that particular location. Types of trees Binary search tree A Binary Search Tree is a node-based data structure where each node contains a key and two su ...
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Red–black Tree
In computer science, a red–black tree is a self-balancing binary search tree data structure noted for fast storage and retrieval of ordered information. The nodes in a red-black tree hold an extra "color" bit, often drawn as red and black, which help ensure that the tree is always approximately balanced. When the tree is modified, the new tree is rearranged and "repainted" to restore the coloring properties that constrain how unbalanced the tree can become in the worst case. The properties are designed such that this rearranging and recoloring can be performed efficiently. The (re-)balancing is not perfect, but guarantees searching in O(\log n) time, where n is the number of entries in the tree. The insert and delete operations, along with tree rearrangement and recoloring, also execute in O(\log n) time. Tracking the color of each node requires only one bit of information per node because there are only two colors (due to memory alignment present in some programming languag ...
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Map (computer Science)
In computer science, an associative array, key-value store, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with ''finite'' domain. It supports 'lookup', 'remove', and 'insert' operations. The dictionary problem is the classic problem of designing efficient data structures that implement associative arrays. The two major solutions to the dictionary problem are hash tables and search trees..Dietzfelbinger, M., Karlin, A., Mehlhorn, K., Meyer auf der Heide, F., Rohnert, H., and Tarjan, R. E. 1994"Dynamic Perfect Hashing: Upper and Lower Bounds". SIAM J. Comput. 23, 4 (Aug. 1994), 738-761. http://portal.acm.org/citation.cfm?id=182370 It is sometimes also possible to solve the problem using directly addressed arrays, binary search trees, or other more specialized structures. Many programming ...
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Set (abstract Data Type)
In computer science, a set is an abstract data type that can store unique values, without any particular sequence, order. It is a computer implementation of the mathematics, mathematical concept of a finite set. Unlike most other collection (abstract data type), collection types, rather than retrieving a specific element from a set, one typically tests a value for membership in a set. Some set data structures are designed for static or frozen sets that do not change after they are constructed. Static sets allow only query operations on their elements — such as checking whether a given value is in the set, or enumerating the values in some arbitrary order. Other variants, called dynamic or mutable sets, allow also the insertion and deletion of elements from the set. A multiset is a special kind of set in which an element can appear multiple times in the set. Type theory In type theory, sets are generally identified with their indicator function (characteristic function): accord ...
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Real-time Deque
In computer science, a double-ended queue (abbreviated to deque, ) is an abstract data type that generalizes a queue, for which elements can be added to or removed from either the front (head) or back (tail). It is also often called a head-tail linked list, though properly this refers to a specific data structure ''implementation'' of a deque (see below). Naming conventions ''Deque'' is sometimes written ''dequeue'', but this use is generally deprecated in technical literature or technical writing because ''dequeue'' is also a verb meaning "to remove from a queue". Nevertheless, several libraries and some writers, such as Aho, Hopcroft, and Ullman in their textbook ''Data Structures and Algorithms'', spell it ''dequeue''. John Mitchell, author of ''Concepts in Programming Languages,'' also uses this terminology. Distinctions and sub-types This differs from the queue abstract data type or ''first in first out'' list ( FIFO), where elements can only be added to one end and ...
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Real-time Queue
In computer science, a queue is a collection of entities that are maintained in a sequence and can be modified by the addition of entities at one end of the sequence and the removal of entities from the other end of the sequence. By convention, the end of the sequence at which elements are added is called the back, tail, or rear of the queue, and the end at which elements are removed is called the head or front of the queue, analogously to the words used when people line up to wait for goods or services. The operation of adding an element to the rear of the queue is known as ''enqueue'', and the operation of removing an element from the front is known as ''dequeue''. Other operations may also be allowed, often including a ''peek'' or ''front'' operation that returns the value of the next element to be dequeued without dequeuing it. The operations of a queue make it a first-in-first-out (FIFO) data structure. In a FIFO data structure, the first element added to the queue will b ...
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Singly Linked List
In computer science, a linked list is a linear collection of data elements whose order is not given by their physical placement in memory. Instead, each element points to the next. It is a data structure consisting of a collection of nodes which together represent a sequence. In its most basic form, each node contains data, and a reference (in other words, a ''link'') to the next node in the sequence. This structure allows for efficient insertion or removal of elements from any position in the sequence during iteration. More complex variants add additional links, allowing more efficient insertion or removal of nodes at arbitrary positions. A drawback of linked lists is that data access time is linear in respect to the number of nodes in the list. Because nodes are serially linked, accessing any node requires that the prior node be accessed beforehand (which introduces difficulties in pipelining). Faster access, such as random access, is not feasible. Arrays have better cache lo ...
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Store-passing Style
Store-passing style is a programming technique that is used to model mutable state without using mutable state. It generally arises in the conversion of imperative programs into purely functional ones. So, for instance, consider this JavaScript program, written in a non-store-passing-style: var lastWasA = false // a treebin represents a binary tree of strings. // a treebin is either // - a string, or // - // does an in-order traversal of this tree's // leaves contain an 'a' followed by a 'b'? function aThenB(treebin) This contains a reference to a global variable. In store-passing style, the value of the global variable (or variables) is passed along to each call, and also returned from each call and threaded through the next call. The code might look like this: function aThenB(treebin, lastWasA) Note that each call takes an extra argument, and two values are now returned; the ordinary return value, and a new value representing the state of the formerly mutable vari ...
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Class (computer Programming)
In object-oriented programming, a class defines the shared aspects of objects created from the class. The capabilities of a class differ between programming languages, but generally the shared aspects consist of state ( variables) and behavior ( methods) that are each either associated with a particular object or with all objects of that class. Object state can differ between each instance of the class whereas the class state is shared by all of them. The object methods include access to the object state (via an implicit or explicit parameter that references the object) whereas class methods do not. If the language supports inheritance, a class can be defined based on another class with all of its state and behavior plus additional state and behavior that further specializes the class. The specialized class is a ''sub-class'', and the class it is based on is its ''superclass''. Attributes Object lifecycle As an instance of a class, an object is constructed from a class via '' ...
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