Communication

9 relations: AVL tree, B-tree, Binary search tree, Computer science, Red–black tree, Scapegoat tree, Self-balancing binary search tree, 2–3 tree, 2–3–4 tree.

AVL tree

In computer science, an AVL tree (named after inventors Adelson-Velsky and Landis) is a self-balancing binary search tree.

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B-tree

In computer science, a B-tree is a self-balancing tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time.

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Binary search tree

In computer science, binary search trees (BST), sometimes called ordered or sorted binary trees, are a particular type of container: data structures that store "items" (such as numbers, names etc.) in memory.

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Computer science

Computer science deals with the theoretical foundations of information and computation, together with practical techniques for the implementation and application of these foundations.

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Red–black tree

A red–black tree is a kind of self-balancing binary search tree in computer science.

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Scapegoat tree

In computer science, a scapegoat tree is a self-balancing binary search tree, invented by Arne Andersson and again by Igal Galperin and Ronald L. Rivest.

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Self-balancing binary search tree

In computer science, a self-balancing (or height-balanced) binary search tree 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.

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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.

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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 is commonly used to implement dictionaries.

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Redirects here:

AA trees, Aa tree, Aa trees, Andersson tree.

References

[1] https://en.wikipedia.org/wiki/AA_tree

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