1. Introduction to C Programming CE00312-1 Lecture 23 Binary Trees

2. Binary Search Tree A binary tree has a maximum of two branches. A binary search tree has some further characteristics: 1)With respect to any particular node in the tree, all those nodes in the left sub-tree have data which are less (alphabetically for strings) than the node, and all those in the right sub-tree are greater.

3. A Binary Search Tree teddy fred nick darryl fong thomas rob brian colin a leaf root of tree

4. Searching a Binary Search Tree 2)A search for a particular data item, only involves searching down one branch at each node. In the example, searching for “fong” involves going left at “fred” (“fong” < “fred”), then right at “colin” (“fong” > “colin”), then right at “darryl” (“fong” > “darryl”) and then finding “fong” as a leaf.

5. Inserting into a Binary Search Tree teddy fred nick darryl fong thomas rob brian colin claude node to insert a leaf root of tree

6. Insertion into a Binary Search Tree 3)Insertion of a new node is similar to a search, and then linking in a new leaf for that node. In the example, a new node for “claude” would be inserted to the right of “brian”, because “claude” is less than both “fred” and “colin” but not “brian”. 4)An Inorder Traversal of the tree yields all the nodes in order (alphabetical for strings).

7. Efficiency Searching, insertion, deletion and sorting (see below) are efficient because half the tree is eliminated at each comparison (cf binary search with arrays). In searching for an item in a binary search tree only involves going left or right for each node as we descend the tree. This is similar to choosing first or second half during a binary search for an array. Eliminating half the data with each comparison implies the total number of comparisons is log 2 n for n items. However, this is only guaranteed if the tree is balanced!

8. A Binary Tree as a Linked List fred teddy nick NULLNULL NULLNULL NULLNULL NULLNULL NULLNULL root darryl

9. Structure of a tree node leftrightdata left sub-tree right sub-tree

10. Header for Binary Search Tree Let us define a header file called “tree.h” containing all our types, structures and tree function prototypes. This file can be included in all files that need to use binary search trees. We shall also keep all our tree functions in “tree.c” and an application in “treegrow.c”. All these may be compiled by: cc treegrow.c tree.c

11. Header file “tree.h” #include "stdio.h“// for I/O and NULL #include "stdlib.h“// for malloc #include "string.h"// for strings struct node { struct node *left; // left branch char data[21];// string data struct node *right;// right branch }; typedef struct node *Treepointer; // new type called Treepointer

12. Prototypes for binary search trees void inorder(Treepointer); // traverse tree void insert(Treepointer, Treepointer); // insert a node into a tree Treepointer createnode(char []); // create a node for an item Treepointer delete(Treepointer, char []); // delete an item from a tree

13. Inorder Traversal A traversal involves visiting all the nodes in the tree in a particular sequence. The most commonly used one is the inorder traversal. Inorder traversal 1. visits all the nodes to left of the given node, 2. then the given node itself and 3. then visits all those to the right. For a binary search tree this yields the data in sort order.

14. Traversing a binary search tree teddy fred nick darryl fong thomas rob brian colin a leaf root of tree

15. Traversals are recursive Any function that visits all the nodes in a tree has to be recursive. All traversal algorithms should be recursive. Iterative (using while loops) solutions are extremely cumbersome - not to mention very difficult - to write. This should be expected because trees themselves are recursive data structures - every tree has branches which are themselves subtrees.

16. Inorder Traversal #include "tree.h" void inorder(Treepointer T) {// traverse the tree, T if (T != NULL) { inorder(T -> left); // traverse left printf("%s\n", T -> data);// print data inorder(T -> right); // traverse right }//else empty tree do nothing } To print all nodes in alphabetical order use: inorder (root);

17. Algebraic Trees

20. Inorder Traversal can give the same result for different trees. Using the normal infix notation, brackets would have to be used to distinguish (A + B) * CfromA + B * C E.G. (2 + 3) * 4 2 + 3 * 4 Give 2014

21. Reverse Polish However, postorder traversal gives different results for different trees. Thus, reverse polish notation can represent algebraic trees faithfully without the use of either brackets or operator precedences! A B + C *(do A B + first) is different from A B C * +(do B C * first) Hence the use of reverse polish by compilers

22. Postorder traversal Postorder traversal is almost the same as inorder traversal – both have to visit all the same nodes – but in a different sequence. The recursive algorithm should be very similar as the two traversals do similar things. Only two statements are swapped, so that for a postorder traversal, the right subtree is visited before printing the current node, T.

23. Postorder Traversal #include "tree.h" void postorder(Treepointer T) {// traverse the tree, T if (T != NULL) { postorder(T -> left); // traverse left postorder(T -> right);// traverse right printf("%s ", T -> data);// print data }//else empty tree do nothing } To print all nodes in reverse polish use: postorder (root);