I can only think of one at the moment: It's a slow way of finding data. Let's say you have an employee tree, the CEO (Parent root) at the top, two children (Both managers), and each child has a further three children (Employees). If you had to find a certain employee, some trees force you to follow a certain path in order to locate them, some are more efficient that others, whilst some may take a long time.
1. pre-order b-tree traversal. 2. in-order b-tree traversal. 3. post-order b-tree traversal
Because a tree is a recursive data-structure. It's easier to write (and easier to understand) a recursive program for handling it.
In order traversal is used.
A binary search tree is already ordered. An in order traversal will give you a sorted list of nodes.
By using Depth First Search or Breadth First search Tree traversal algorithm we can print data in Binary search tree.
1. pre-order b-tree traversal. 2. in-order b-tree traversal. 3. post-order b-tree traversal
Because a tree is a recursive data-structure. It's easier to write (and easier to understand) a recursive program for handling it.
In order traversal is used.
tree? oh its tree
A binary search tree is already ordered. An in order traversal will give you a sorted list of nodes.
any body can help on this ?
By using Depth First Search or Breadth First search Tree traversal algorithm we can print data in Binary search tree.
A binary tree variant that allows fast traversal: given a pointer to a node in a threaded tree, it is possible to cheaply find its in-order successor (and/or predecessor).
i will killl u
You don't need it. Think about it, you can just use a stack (or a recursive function.)
In-order traversal relates to non-empty binary trees which can be traversed in one of three ways: pre-order, in-order and post-order. The current node is always regarded as being the root of the traversal, and all operations occur recursively upon that root. Pre-order: 1. Visit the root. 2. Traverse the left sub-tree. 3. Traverse the right sub-tree. In-order: 1. Traverse the left sub-tree. 2. Visit the root. 3. Traverse the right sub-tree. Post-order: 1. Traverse the left sub-tree. 2. Traverse the right sub-tree. 3. Visit the root.
FAEKCDHGB