Trees

1. A tree is a set of nodes which are connected by branches to other nodes in a 'tree-like' structure. There is a special node called the root from which all other nodes can be accessed. Other nodes are grouped into subtrees which in turn form other subtrees and so on. The tree shown in figure 1 has a variable number of branches from each node and may not be a practical structure to implement. A special tree with more than two branches can be implemented as a B Tree. A tree with a maximum of two branches is known as a Binary Tree. A Strict Binary Tree has either none or two branches. Trees

2. Tree diagram figure 1

3. A Knuth Binary Tree has none, one or two branches. Figure 2 shows a Knuth Binary Tree. Each node contains two pointers, one pointing to the left subtree and one pointing to the right subtree. A Knuth Tree is easier to implement than a strict binary tree as recursive algorithms can be used. In a Binary Search Tree the values contained in the nodes in the left subtree, child nodes, will all be less than that in the root node. Similarly the values contained in the nodes in the right subtree will all be greater than that in the root node. Trees can be reversed if required by making the left subtrees contain larger values than the root. Knuth Binary Trees

4. Knuth binary tree figure 2

5. Figure 3 shows the order of the nodes in a example of a binary search tree. The letters symbolise the order of the nodes. In a balanced tree the root node would be approximately midway in an ordered list of the contents of the nodes. Nodes with lower values than the root are found in the left subtree and higher values in the right subtree. Each subtree follows the same rule. Binary search tree

6. Binary search tree figure 3

7. A traverse is an ordered walk through a tree such that each node is visited only once. There are various ways of traversing a tree. Using figure 3 as an example: Traversing a Tree

8. If the tree is empty then make this item the tree else compare the item to the root if the item comes before the root add item to the left branch end if if the item comes after the root (if item is not unique need to use an else to allow for equality)‏ add item to the right branch end if end if Algorithm for constructing a tree (adding a unique node)‏

9. if the tree is not empty and not found if the key sought equals the root's key then found is true else if the key sought is less than the root's key then search down the left tree else search down the right tree end if end if end if Algorithm for searching a tree

10. There are 4 cases: 1. The node is a leaf 2. The node has only one branch 3. The node has 2 branches and the Rightmost Node of the Left Subtree (RNLS) is a leaf 4. The node has 2 branches and the RNLS has a left subtree Deleting an item from a tree

11. Free the space occupied by the leaf node. Make pointer to the node from the parent node ==NULL. Case 1 - the node is a leaf

12. Graft the child branch of the node onto the parent node. Free the space occupied by the deleted node. Case 2: The node has 1 branch

13. Copy data part of the RNLS to data part of node to be deleted Free the space occupied by the RNLS Make pointer to the RNLS from it's parent == NULL Case 3: The node has 2 branches and the Rightmost Node of the Left Subtree (RNLS) is a leaf

14. Copy data part of RNLS to data part of node to be deleted Graft the child branch of the RNLS (can only be a left branch) onto the RNLS's parent node. Free the space occupied by the RNLS Case 4: The node has 2 branches and the RNLS has a left subtree

15. tree.csource1Global declarations

16. tree.csource2main()‏

17. tree.csource3chop()pause()menu()‏

18. tree.csource4display,getentryfunctions

19. tree.csource5insert,find_delfunctions

20. tree.c source 6 delet() function

21. tree.csource7whichcase() function