Walk Tree vs Zhang and Sasha Algorithms
I need some help understanding how two tree comparing algorithms differ. I am working with Microsoft’s XmlDiffPatch (http://msdn.microsoft.com/en-us/library/aa302294.aspx) which compares two xmls. The library has some pretty bad documentation IMO however you can find some info here: (http://devproconnections.com/aspnet/compare-and-patch-xml-documents).
Algorithm for sport tournament bracket tree
I would like to develop a library that:
Algorithm for sport tournament bracket tree
I would like to develop a library that:
Where to put data for tree structure which every node requires?
I have a quad-tree structure where each node has some of its own data, but there is also data which applies to the tree as a whole.
Where to put data for tree structure which every node requires?
I have a quad-tree structure where each node has some of its own data, but there is also data which applies to the tree as a whole.
How to randomly get or find a sub-tree (include root node) from a given tree that contains n leaf-nodes
I have a non-binary tree.
I want to randomly find a “sub-trees” that are connected from root to leaf which must have at least n leaf-nodes (leaf-nodes of sub-tree must be leaf-nodes of given tree).
For example: given a tree as below
How to randomly get or find a sub-tree (include root node) from a given tree that contains n leaf-nodes
I have a non-binary tree.
I want to randomly find a “sub-trees” that are connected from root to leaf which must have at least n leaf-nodes (leaf-nodes of sub-tree must be leaf-nodes of given tree).
For example: given a tree as below
How to randomly get or find a sub-tree (include root node) from a given tree that contains n leaf-nodes
I have a non-binary tree.
I want to randomly find a “sub-trees” that are connected from root to leaf which must have at least n leaf-nodes (leaf-nodes of sub-tree must be leaf-nodes of given tree).
For example: given a tree as below
Most efficient way to generate all descendents of all nodes in a tree
I’m looking for the most efficient algorithm to take a tree (stored as either a list of edges; OR as a list of mappings from parent node to a list of child nodes); and produce, for EVERY node, a list of all nodes descended from it (leaf level and non-leaf level).
Most efficient way to generate all descendents of all nodes in a tree
I’m looking for the most efficient algorithm to take a tree (stored as either a list of edges; OR as a list of mappings from parent node to a list of child nodes); and produce, for EVERY node, a list of all nodes descended from it (leaf level and non-leaf level).