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An adjacency list representation for a graph associates each vertex in the graph with the collection of its neighbouring vertices or edges. There are many variations of this basic idea, differing in the details of how they implement the association between vertices and collections, in how they implement the collections, in whether they include both vertices and edges or only vertices as first ...
Adjacency list [2] Vertices are stored as records or objects, and every vertex stores a list of adjacent vertices. This data structure allows the storage of additional data on the vertices. Additional data can be stored if edges are also stored as objects, in which case each vertex stores its incident edges and each edge stores its incident ...
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, [ 1 ] [ 2 ] except for the root node, which has no parent (i.e., the ...
Initialize a tree with a single vertex, chosen arbitrarily from the graph. Grow the tree by one edge: Of the edges that connect the tree to vertices not yet in the tree, find the minimum-weight edge, and transfer it to the tree. Repeat step 2 (until all vertices are in the tree).
Object-oriented applications contain complex webs of interrelated objects. Objects are linked to each other by one object either owning or containing another object or holding a reference to another object. This web of objects is called an object graph and it is the more abstract structure that can be used in discussing an application's state.
The main alternative data structure, also in use for this application, is the adjacency list. [11] [12] The space needed to represent an adjacency matrix and the time needed to perform operations on them is dependent on the matrix representation chosen for the underlying matrix.
The article makes the claim: " Besides the space tradeoff, the different data structures also facilitate different operations. It's easy to find all vertices adjacent to a given vertex in an adjacency list representation; you simply read its adjacency list. With an adjacency matrix you must instead scan over an entire row, taking O(n) time.
A list-zipper always represents the entire data structure. However, this information is from the perspective of a specific location within that data structure. Consequently, a list-zipper is a pair consisting of both the location as a context or starting point, and a recording or path that permits reconstruction from that starting location.