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2–3 Tree
In computer science, a 2–3 tree is a tree data structure, where every node with children (internal node) has either two children (2-node) and one data element or three children (3-nodes) and two data elements. A 2–3 tree is a B-tree of order 3. Nodes on the outside of the tree (leaf nodes) have no children and one or two data elements. 2–3 trees were invented by John Hopcroft in 1970. 2–3 trees are required to be balanced, meaning that each leaf is at the same level. It follows that each right, center, and left subtree of a node contains the same or close to the same amount of data. Definitions We say that an internal node is a 2-node if it has ''one'' data element and ''two'' children. We say that an internal node is a 3-node if it has ''two'' data elements and ''three'' children. A 4-node, with three data elements, may be temporarily created during manipulation of the tree but is never persistently stored in the tree. Image:2-3-4 tree 2-node.svg, 2 node Image:2-3-4-t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Hopcroft
John Edward Hopcroft (born October 7, 1939) is an American theoretical computer scientist. His textbooks on theory of computation (also known as the Cinderella book) and data structures are regarded as standards in their fields. He is the IBM Professor of Engineering and Applied Mathematics in Computer Science at Cornell University, Co-Director of the Center on Frontiers of Computing Studies at Peking University, and the Director of the John Hopcroft Center for Computer Science at Shanghai Jiao Tong University. Education He received his bachelor's degree from Seattle University in 1961. He received his master's degree and Ph.D. from Stanford University in 1962 and 1964, respectively. He worked for three years at Princeton University and since then has been at Cornell University. Hopcroft is the grandson of Jacob Nist, founder of the Seattle-Tacoma Box Company. Career In addition to his research work, he is well known for his books on algorithms and formal languages coauthored w ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
(a,b)-tree
In computer science, an (a,b) tree is a kind of balanced search tree. An (a,b)-tree has all of its leaves at the same depth, and all internal nodes except for the root have between and children, where and are integers such that . The root has, if it is not a leaf, between 2 and children. Definition Let , be positive integers such that . Then a rooted tree is an (a,b)-tree when: * Every inner node except the root has at least and at most children. * The root has at most children. * All paths from the root to the leaves are of the same length. Internal node representation Every internal node of a (a,b)-tree has the following representation: * Let \rho_v be the number of child nodes of node . * Let S_v \dots \rho_v/math> be pointers to child nodes. * Let H_v \dots \rho_v - 1/math> be an array of keys such that H_v /math> equals the largest key in the subtree pointed to by S_v /math>. See also *B-tree In computer science, a B-tree is a self-balancing tree data st ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AA Tree
An AA tree in computer science is a form of balanced tree used for storing and retrieving ordered data efficiently. AA trees are named after Arne Andersson, the one who theorized them. AA trees are a variation of the red–black tree, a form of binary search tree which supports efficient addition and deletion of entries. Unlike red–black trees, red nodes on an AA tree can only be added as a right subchild. In other words, no red node can be a left sub-child. This results in the simulation of a 2–3 tree instead of a 2–3–4 tree, which greatly simplifies the maintenance operations. The maintenance algorithms for a red–black tree need to consider seven different shapes to properly balance the tree: An AA tree on the other hand only needs to consider two shapes due to the strict requirement that only right links can be red: Balancing rotations Whereas red–black trees require one bit of balancing metadata per node (the color), AA trees require O(log(log(N))) bits o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
2–3 Heap
In computer science, a 2–3 heap is a data structure, a variation on the heap, designed by Tadao Takaoka in 1999. The structure is similar to the Fibonacci heap, and borrows from the 2–3 tree. Time costs for some common heap operations are: * ''Delete-min'' takes O(\log(n)) amortized time In computer science, amortized analysis is a method for analyzing a given algorithm's complexity, or how much of a resource, especially time or memory, it takes to execute. The motivation for amortized analysis is that looking at the worst-case .... * ''Decrease-key'' takes constant amortized time. * ''Insertion'' takes constant amortized time. Polynomial of trees A linear tree of size r is a sequential path of r nodes with the first node as a root of the tree and it is represented by a bold \mathbf (e.g. \mathbf is a linear tree of a single node). Product P = ST of two trees S and T, is a new tree with every node of S is replaced by a copy of T and for each edge of S we connect the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
2–3–4 Tree
In computer science, a 2–3–4 tree (also called a 2–4 tree) is a self-balancing data structure that can be used to implement dictionaries. The numbers mean a tree where every node with children (internal node) has either two, three, or four child nodes: * a 2-node has one data element, and if internal has two child nodes; * a 3-node has two data elements, and if internal has three child nodes; * a 4-node has three data elements, and if internal has four child nodes; Image:2-3-4-tree-2-node.svg, 2-node Image:2-3-4-tree-3-node.svg, 3-node Image:2-3-4-tree-4-node.svg, 4-node 2–3–4 trees are B-trees of order 4; like B-trees in general, they can search, insert and delete in O(log ''n'') time. One property of a 2–3–4 tree is that all external nodes are at the same depth. 2–3–4 trees are isomorphic to red–black trees, meaning that they are equivalent data structures. In other words, for every 2–3–4 tree, there exists at least one and at most one red–bla ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Red–black Tree
In computer science, a red–black tree is a kind of self-balancing binary search tree. Each node stores an extra bit representing "color" ("red" or "black"), used to ensure that the tree remains balanced during insertions and deletions. 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. The insert and delete operations, along with the tree rearrangement and recoloring, are also performed 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. The tree does not contain any other data specific to it being a red–black tree, so its memory footprint is almost identical to that of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Red–black Tree
In computer science, a red–black tree is a kind of self-balancing binary search tree. Each node stores an extra bit representing "color" ("red" or "black"), used to ensure that the tree remains balanced during insertions and deletions. 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. The insert and delete operations, along with the tree rearrangement and recoloring, are also performed 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. The tree does not contain any other data specific to it being a red–black tree, so its memory footprint is almost identical to that of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binary Search Tree
In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree. The time complexity of operations on the binary search tree is directly proportional to the height of the tree. Binary search trees allow binary search for fast lookup, addition, and removal of data items. Since the nodes in a BST are laid out so that each comparison skips about half of the remaining tree, the lookup performance is proportional to that of binary logarithm. BSTs were devised in the 1960s for the problem of efficient storage of labeled data and are attributed to Conway Berners-Lee and David Wheeler. The performance of a binary search tree is dependent on the order of insertion of the nodes into the tree since arbitrary insertions may lead to degeneracy; several variations of the bi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Science
Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to Applied science, practical disciplines (including the design and implementation of Computer architecture, hardware and Computer programming, software). Computer science is generally considered an area of research, academic research and distinct from computer programming. 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 for preventing Vulnerability (computing), security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Progr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tree (data Structure)
In computer science, a tree is a widely used abstract data type that represents a hierarchical tree structure with a set of connected nodes. Each node in the tree can be connected to many children (depending on the type of tree), but must be connected to exactly one parent, except for the ''root'' node, which has no parent. These constraints mean there are no cycles or "loops" (no node can be its own ancestor), and also that each child can be treated like the root node of its own subtree, making recursion a useful technique for tree traversal. In contrast to linear data structures, many trees cannot be represented by relationships between neighboring nodes in a single straight line. Binary trees are a commonly used type, which constrain the number of children for each parent to exactly two. When the order of the children is specified, this data structure corresponds to an ordered tree in graph theory. A value or pointer to other data may be associated with every node in the tre ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Leaf Node
In computer science, a tree is a widely used abstract data type that represents a hierarchical tree structure with a set of connected nodes. Each node in the tree can be connected to many children (depending on the type of tree), but must be connected to exactly one parent, except for the ''root'' node, which has no parent. These constraints mean there are no cycles or "loops" (no node can be its own ancestor), and also that each child can be treated like the root node of its own subtree, making recursion a useful technique for tree traversal. In contrast to linear data structures, many trees cannot be represented by relationships between neighboring nodes in a single straight line. Binary trees are a commonly used type, which constrain the number of children for each parent to exactly two. When the order of the children is specified, this data structure corresponds to an ordered tree in graph theory. A value or pointer to other data may be associated with every node in the tree ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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