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Dynamic Algorithm
Dynamic problems in computational complexity theory are problems stated in terms of the changing input data. In the most general form a problem in this category is usually stated as follows: * Given a class of input objects, find efficient algorithms and data structures to answer a certain query about a set of input objects each time the input data is modified, i.e., objects are inserted or deleted. Problems of this class have the following measures of complexity: * Space the amount of Memory space (computational resource), memory space required to store the data structure; * Initialization time time required for the initial construction of the data structure; * Insertion time time required for the update of the data structure when one more input element is added; * Deletion time time required for the update of the data structure when an input element is deleted; * Query time time required to answer a query; * Other operations specific to the problem in question The overall set o ...
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Computational Complexity Theory
In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying their computational complexity, i.e., the amount of resources needed to solve them, such as time and storage. Other measures of complexity are also used, such as the amount of communication (used in communication complexity), the number of gates in a circuit (used in circuit complexity) and the number of processors (used in parallel computing). One of the roles of computationa ...
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Memory Space (computational Resource)
In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems. The simplest computational resources are computation time, the number of steps necessary to solve a problem, and memory space, the amount of storage needed while solving the problem, but many more complicated resources have been defined. A computational problem is generally defined in terms of its action on any valid input. Examples of problems might be "given an integer ''n'', determine whether ''n'' is prime", or "given two numbers ''x'' and ''y'', calculate the product ''x''*''y''". As the inputs get bigger, the amount of computational resources needed to solve a problem will increase. Thus, the resources needed to solve a problem are described in terms of asymptotic analysis, by identifying the resources as a function of the length or size of the input. Resource usage is often partially quantified using Big O notation. Co ...
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Online Algorithm
In computer science, an online algorithm is one that can process its input piece-by-piece in a serial fashion, i.e., in the order that the input is fed to the algorithm, without having the entire input available from the start. In contrast, an offline algorithm is given the whole problem data from the beginning and is required to output an answer which solves the problem at hand. In operations research, the area in which online algorithms are developed is called online optimization. As an example, consider the sorting algorithms selection sort and insertion sort: selection sort repeatedly selects the minimum element from the unsorted remainder and places it at the front, which requires access to the entire input; it is thus an offline algorithm. On the other hand, insertion sort considers one input element per iteration and produces a partial solution without considering future elements. Thus insertion sort is an online algorithm. Note that the final result of an insertion sort ...
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Self-balancing Binary Search 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 \mathcal 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. Se ...
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Priority Queue
In computer science, a priority queue is an abstract data-type similar to a regular queue or stack data structure in which each element additionally has a ''priority'' associated with it. In a priority queue, an element with high priority is served before an element with low priority. In some implementations, if two elements have the same priority, they are served according to the order in which they were enqueued; in other implementations ordering of elements with the same priority remains undefined. While coders often implement priority queues with heaps, they are conceptually distinct from heaps. A priority queue is a concept like a list or a map; just as a list can be implemented with a linked list or with an array, a priority queue can be implemented with a heap or with a variety of other methods such as an unordered array. Operations A priority queue must at least support the following operations: * ''is_empty'': check whether the queue has no elements. * ''insert_wi ...
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Giuseppe F
Giuseppe is the Italian form of the given name Joseph, from Latin Iōsēphus from Ancient Greek Ἰωσήφ (Iōsḗph), from Hebrew יוסף. It is the most common name in Italy and is unique (97%) to it. The feminine form of the name is Giuseppina. People with the given name Artists and musicians * Giuseppe Aldrovandini (1671–1707), Italian composer * Giuseppe Arcimboldo (1526 or 1527–1593), Italian painter * Giuseppe Belli (singer) (1732–1760), Italian castrato singer * Giuseppe Gioachino Belli (1791–1863), Italian poet * Giuseppe Castiglione (1829–1908) (1829–1908), Italian painter * Giuseppe Giordani (1751–1798), Italian composer, mainly of opera * Giuseppe Ottaviani (born 1978), Italian musician and disc jockey * Giuseppe Psaila (1891–1960), Maltese Art Nouveau architect * Giuseppe Sammartini (1695–1750), Italian composer and oboist * Giuseppe Sanmartino or Sammartino (1720–1793), Italian sculptor * Giuseppe Santomaso (1907–1990), Italian painter * G ...
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Dynamization
In computer science, dynamization is the process of transforming a static data structure into a dynamic one. Although static data structures may provide very good functionality and fast queries, their utility is limited because of their inability to grow/shrink quickly, thus making them inapplicable for the solution of dynamic problems, where the amount of the input data changes. Dynamization techniques provide uniform ways of creating dynamic data structures. Decomposable search problems We define problem P of searching for the predicate M match in the set S as P(M,S). Problem P is ''decomposable'' if the set S can be decomposed into subsets S_i and there exists an operation + of result unification such that P(M,S) = P(M,S_0) + P(M,S_1) + \dots + P(M,S_n). Decomposition Decomposition is a term used in computer science to break static data structures into smaller units of unequal size. The basic principle is the idea that any decimal number can be translated into a representation ...
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Dynamic Connectivity
In computing and graph theory, a dynamic connectivity structure is a data structure that dynamically maintains information about the connected components of a graph. The set ''V'' of vertices of the graph is fixed, but the set ''E'' of edges can change. The three cases, in order of difficulty, are: * Edges are only added to the graph (this can be called ''incremental connectivity''); * Edges are only deleted from the graph (this can be called ''decremental connectivity''); * Edges can be either added or deleted (this can be called ''fully dynamic connectivity''). After each addition/deletion of an edge, the dynamic connectivity structure should adapt itself such that it can give quick answers to queries of the form "is there a path between ''x'' and ''y''?" (equivalently: "do vertices ''x'' and ''y'' belong to the same connected component?"). Incremental connectivity If edges can only be added, then the dynamic connectivity problem can be solved by a Disjoint-set data structure. ...
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Kinetic Data Structure
A kinetic data structure is a data structure used to track an attribute of a geometric system that is moving continuously. For example, a kinetic convex hull data structure maintains the convex hull of a group of n moving points. The development of kinetic data structures was motivated by computational geometry problems involving physical objects in continuous motion, such as collision or visibility detection in robotics, animation or computer graphics. Overview Kinetic data structures are used on systems where there is a set of values that are changing as a function of time, in a known fashion. So the system has some values, and for each value v, it is known that v=f(t). Kinetic data structures allow queries on a system at the current virtual time t, and two additional operations: *\textrm(t): Advances the system to time t. *\textrm(v,f(t)): Alters the trajectory of value v to f(t), as of the current time. Additional operations may be supported. For example, kinetic data stru ...
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Computational Complexity Theory
In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying their computational complexity, i.e., the amount of resources needed to solve them, such as time and storage. Other measures of complexity are also used, such as the amount of communication (used in communication complexity), the number of gates in a circuit (used in circuit complexity) and the number of processors (used in parallel computing). One of the roles of computationa ...
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