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In particular, we can adjust it to merge (link) and split (cut) in O(log(n)) amortized time. Link/cut trees divide each tree in the represented forest into vertex-disjoint paths, where each path is represented by an auxiliary data structure (often splay trees, though the original paper predates splay trees and thus uses biased binary search ...
Trees are commonly used to represent or manipulate hierarchical data in applications such as: File systems for: Directory structure used to organize subdirectories and files (symbolic links create non-tree graphs, as do multiple hard links to the same file or directory) The mechanism used to allocate and link blocks of data on the storage device
A cutpoint, cut vertex, or articulation point of a graph G is a vertex that is shared by two or more blocks. The structure of the blocks and cutpoints of a connected graph can be described by a tree called the block-cut tree or BC-tree. This tree has a vertex for each block and for each articulation point of the given graph.
Label each split component with a P (a two-vertex split component with multiple edges), an S (a split component in the form of a triangle), or an R (any other split component). While there exist two split components that share a linked pair of virtual edges, and both components have type S or both have type P, merge them into a single larger ...
In computer science, tree traversal (also known as tree search and walking the tree) is a form of graph traversal and refers to the process of visiting (e.g. retrieving, updating, or deleting) each node in a tree data structure, exactly once. Such traversals are classified by the order in which the nodes are visited.
A recursive tree is a labeled rooted tree where the vertex labels respect the tree order (i.e., if u < v for two vertices u and v, then the label of u is smaller than the label of v). In a rooted tree, the parent of a vertex v is the vertex connected to v on the path to the root; every vertex has a unique parent, except the root has no parent. [24]
B+ tree node format where K=4. (p_i represents the pointers, k_i represents the search keys). As with other trees, B+ trees can be represented as a collection of three types of nodes: root, internal (a.k.a. interior), and leaf. In B+ trees, the following properties are maintained for these nodes:
Create a forest (a set of trees) initially consisting of a separate single-vertex tree for each vertex in the input graph. Sort the graph edges by weight. Loop through the edges of the graph, in ascending sorted order by their weight. For each edge: Test whether adding the edge to the current forest would create a cycle.