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B-trees were invented by Rudolf Bayer and Edward M. McCreight while working at Boeing Research Labs to efficiently manage index pages for large random-access files. The basic assumption was that indices would be so voluminous that only small chunks of the tree could fit in main memory.
Random binary tree, binary trees with various random distributions, including trees formed by random insertion orders, and trees that are uniformly distributed with a given number of nodes Random recursive tree , increasingly labelled trees, which can be generated using a simple stochastic growth rule.
A tree whose root node has two subtrees, both of which are full binary trees. A perfect binary tree is a binary tree in which all interior nodes have two children and all leaves have the same depth or same level (the level of a node defined as the number of edges or links from the root node to a node). [18] A perfect binary tree is a full ...
Binary trees may also be studied with all nodes unlabeled, or with labels that are not given in sorted order. For instance, the Cartesian tree data structure uses labeled binary trees that are not necessarily binary search trees. [4] A random binary tree is a random tree drawn from a certain probability distribution on binary trees. In many ...
A B+ tree consists of a root, internal nodes and leaves. [1] The root may be either a leaf or a node with two or more children. A B+ tree can be viewed as a B-tree in which each node contains only keys (not key–value pairs), and to which an additional level is added at the bottom with linked leaves.
In computer science, corecursion is a type of operation that is dual to recursion.Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case.
A one-node tree is created for each and a pointer to the corresponding tree is pushed onto the stack. Creating a one-node tree. Continuing, a '+' is read, and it merges the last two trees. Merging two trees. Now, a '*' is read. The last two tree pointers are popped and a new tree is formed with a '*' as the root. Forming a new tree with a root
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;