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An internal node (also known as an inner node, inode for short, or branch node) is any node of a tree that has child nodes. Similarly, an external node (also known as an outer node, leaf node, or terminal node) is any node that does not have child nodes. The height of a node is the length of the longest downward path to a leaf from that node ...
Child: A child node is a node extending from another node. For example, a computer with internet access could be considered a child node of a node representing the internet. The inverse relationship is that of a parent node. If node C is a child of node A, then A is the parent node of C. Degree: the degree of a node is the number of children of ...
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.
An entire binary search tree can be easily traversed in order of the main key, but given only a pointer to a node, finding the node which comes next may be slow or impossible. For example, leaf nodes by definition have no descendants, so given only a pointer to a leaf node no other node can be reached.
Leaf Node - Any node that has no children. Parent Node - Any node connected by a directed edge to its child or children. Child Node - Any node connected to a parent node by a directed edge. Depth - Length of the path from the root to the node. The set of all nodes at a given depth is sometimes called a level of the tree. The root node is at ...
The general class includes variations such as the B+ tree, the B * tree and the B *+ tree. In the B+ tree, the internal nodes do not store any pointers to records, thus all pointers to records are stored in the leaf nodes. In addition, a leaf node may include a pointer to the next leaf node to speed up sequential access. [2]
record Node { data; // The data being stored in the node Node next // A reference [2] to the next node, null for last node } record List { Node firstNode // points to first node of list; null for empty list} Traversal of a singly linked list is simple, beginning at the first node and following each next link until reaching the end:
If no bounding node was found then insert the value into the last node searched if it still fits into it. In this case the new value will either become the new minimum or maximum value. If the value doesn't fit anymore then create a new left or right subtree. If a new node was added then the tree might need to be rebalanced, as described below.