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Chapter 8

Search Trees. Chapter 8. Binary Search Trees. The binary search is a very efficient search algorithm, without insertion and deletion, when we store ordered data in the array structure. When we use linked list, in that case we have to use sequential search as an inefficient search algorithm.

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Chapter 8

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  1. SearchTrees Chapter 8

  2. Binary Search Trees • The binary search is a very efficient search algorithm, without insertion and deletion, when we store ordered data in the array structure. • When we use linked list, in that case we have to use sequential search as an inefficient search algorithm. • Binary search trees provide a suitable structure.

  3. Binary Search Trees Definition • All terms in the left subtree are less than the root. • All terms in the right subtree are greater than or equal to the root. • Each subtree is itself a binary search tree. < K Figure 8-1

  4. Binary Search Trees Figure 8-2

  5. Binary Search Trees Figure 8-3

  6. Binary Search Trees Preorder traversal? Postorder traversal? Inorder traversal? Figure 8-4

  7. Binary Search Trees Binary Search TreesFind the smallest value algorithm findsmallestBST(val root <pointer>) This algorithm finds the smallest node in a BST. PRE root is a pointer to a non-empty BST. Return address of smallest node 1. if (root->left null) 1. return (root) 2. return findsmallestBST(root->left) end findsmallestBST

  8. Binary Search Trees Find the smallest node in BST. Figure 8-5

  9. Binary Search Trees Binary Search TreesFind the largest value algorithm findlargestBST(val root <pointer>) This algorithm finds the larges node in a BST. PRE root is a pointer to a non-empty BST. Return address of largest node 1. if (root->right null) 1. return (root) 2. return findlargestBST(root->right) end findlargestBST

  10. Binary Search Tree Search Finding a specific node in the tree! Figure 8-6

  11. We are looking for node 20. Figure 8-7

  12. Binary Search Trees Binary Search TreesFind the specific value algorithm searchBST(val root <pointer>, val argument <key>) Search a binary search tree for a given value. PRE root is the root to a binary tree or subtree, argument is the key value requested. Return the node address if the value is found, null if the node is not in the tree. 1 If (root is null) 1 return null 2 If (argument < root->key) 1 return searchBST(root->left, argument) 3 else If (argument > root->key) 1 return searchBST(root->right, argument) 4 else 1 return root end searchBST

  13. Binary Search Tree – Insert Node

  14. Binary Search Tree – Insert Node algorithm insertBST(ref root <pointer>, val new <pointer>) Insert node containing new node into BST using iteration PRE root is address of the first node in a BST, new is address of node containing data to be inserted. POST new node inserted into tree.

  15. Binary Search Tree – Insert Node 1 If (root is null) 1 root = new 2 else 1 pwalk = root 2 loop (pwalk not null) 1 parent =pwalk 2 If (new->key < pwalk->key) 1 pwalk=pwalk->left 3 else pwalk=pwalk->right Location for new node found 3 If (new->key < parent->key) 1 parent->left=new 4 else parent->right=new 3 return end insertBST

  16. Binary Search Tree – Delete Node

  17. Binary Search Tree – Delete Node

  18. Binary Search Tree – Delete Node algorithm deleteBST(ref root <pointer>, val dltkey <key>) This algorithm deletes a node from BST. Pre root is pointer to tree containing data to be deleted, dltkey is key of node to be deleted. Post node deleted & memory rcycled, if dltkey not found, root unchanged. Return true if node deleted, false if not found.

  19. Binary Search Tree – Delete Node 1 If (root null) 1 return false 2 If (dltkey < root->key) return deleteBST(root->left, dltkey) 3 else If (dltkey > root->key) return deleteBST(root->right, dltkey) 4 else /*(Delete node found --- Test for leaf node)*/ 1 If (root ->left null) 1 dltprt=root, root =root->right, recycle(dltprt), return true 2 else If (root->right null) 1 dltprt=root, root =root->left, recycle(dltprt), return true 3 else /*Node is not a leaf, find largest node on left subtree*/ 1 dltprt = root->left 2 loop (dltprt->right not null) 1 dltprt=dltprt->right 3 root->data =dltprt->data 4 return deleteBST(root->left, dltprt->data.key) end deleteBST

  20. HW-8 • Create a BST with positive integer numbers which are taken from the screen. • Write the BST delete function which establishes to delete desired node from the BST. • Write the BST list function which lists the nodes in the BST with inorder traversal. • Collect all above functions under a user menu. Load your HW-8 to FTP site until 14 May. 07 at 09:00 am.

  21. AVL Trees In 1962, two Russian mathematicians, G. M. Adelson-Velskil and E. M. Landis created balanced binary tree structure that is named after them – the AVL trees. O(n) O(log2n) |HL-HR| < = 1 Height balanced trees.

  22. AVL Trees – Balancing When we insert a node into a tree or delete a node from a tree, the resulting tree may be unbalanced and we must rebalance it. Figure 8-14 (a and b)

  23. All unbalanced trees fall into one of these four cases: • Left to left • Right to right • Right of left • Left of right

  24. LEFT-OF-LEFT We must balance the left-height tree by rotating the out-of-balance node to the right. Figure 8-15

  25. RIGHT-OF-RIGHT We must balance the right-height tree by rotating the out-of-balance node to the left. Figure 8-16

  26. RIGHT-OF-LEFT • Rotate left • Rotate right Figure 8-17

  27. LEFT-OF-RIGHT • Rotate right • Rotate left Figure 8-18

  28. AVL Node Structure Node key <key type> data <data type> leftsubtree <pointer to Node> rightsubtree <pointer to Node> bal <LH, EH, RH> End Node

  29. AVL Rotate Algorithm algorithm rotateRight( ref root <tree pointer>) This algorithm exchanges pointers to rotate the tree right. PRE root points to tree to be rotated. POST Node rotated and root updated. 1 tempPtr = root->left 2 root->left = tempPtr->right 3 tempPtr->right = root 4 root = tempPtr 5 return end rotateRight

  30. AVL Insert • The search and retrieval algorithms are the same as for any binary tree. • Inorder travelsal is used because AVL trees are search trees. • As a binary search tree, we have to find suitable leaf node on left or right subtree, then we connect new node to this parent node and begin back out of tree. • As we back out of tree we check the balance of each node. If we find unbalanced node we balance it and continue up the tree. • Not all inserts create an out of balance condition.

  31. AVL Insert Algorithm algoritm AVLInsert (ref root <tree pointer>, ref newPtr <tree pointer>, ref taller <boolean>) Using recursion, insert a node into AVL tree. PRE root is a pointer to first node in AVL tree/subtree newPtr is a pointer to new node to be inserted. POST taller is a boolean: true indicating the subtree height has increased, false indicating same height.

  32. AVL Insert Algorithm 1 if (root null) // Insert at root // 1 taller = true 2 root= newPtr 2 else 1 if (newPtr->key < root->key) //left subtree // 1 AVLInsert(root->left, newPtr, taller) 2 if (taller) // insertion is completed and height is changed // 1 if (root left-height) 1 leftBalance(root, taller) 2 else if (root right-height) 1 taller =false 3 adjust balance factor 2 else if (newPtr->key > root->key) //right subtree // 1 AVLInsert(root->right, newPtr, taller) 2 if (taller) // insertion is completed and height is changed // 1 if (root left-height) 1 taller =false 2 else if (root right-height) 1 rihtBalance(root, taller) 3 adjust balance factor 3 else 1 error (“Dupe Data”) 2 recycle(newPtr) 3 taller = false 3 return end AVLInsert

  33. AVL Left Balance Algorithm algorithm leftBalance(ref root <tree pointer>, ref taller <boolean>) This algorithm is entered when the root is left heavy (the left subtree is higher then the right subtree) PRE root is a pointer to the root of the (sub)tree, taller is true. POST root and taller has been updated. 1 leftTree = root->left 2 if (leftTree left-heigh) //Case 1: Left of left, single rotation required. // 1 rotateRight (root) 2 adjust balance factors 3 taller false 3 else // Case 2: Right of left. Double rotation required. // 1 rightTree = leftTree->right 2 adjust balance factors 3 rotateLeft (leftTree) 4 rotateRight (root) 5 taller = false 4 return end leftBalance

  34. AVL Delete Balancing Figure 8-22

  35. Excercise Which of the trees in the following figure is a valid binary search tree and which one is not? Figure 8-25

  36. Excercise Travers the binary search tree using a inorder traversal. Figure 8-26

  37. Excercise The binary search tree was created starting with a null tree and entering data from the keyboard. In what sequence were the data entered? If there is more than one possible sequence, identify the alternatives. Figure 8-27

  38. Excercise The binary search tree was created starting with a null tree and entering data from the keyboard. In what sequence were the data entered? If there is more than one possible sequence, identify the alternatives. Figure 8-28

  39. Excercise Insert 44, 66 and 77 in the binary search tree. Figure 8-29

  40. Excercise Delete the node 60 and then 85 from the tree. Figure 8-30

  41. Excercise Balance the tree. Figure 8-31

  42. Excercise Balance the tree. Figure 8-32

  43. Excercise Add 49 to the AVL tree. The result must be an AVL tree. Show the balance factors in the resulting tree. Figure 8-33

  44. Excercise Add 68 to the AVL tree. The result must be an AVL tree. Show the balance factors in the resulting tree. Figure 8-33

  45. HW-9 • Create an AVL tree with positive integer numbers which are taken from the screen. • Write the AVL delete function which establishes to delete desired node from the AVL. • Write the AVL list function which lists the nodes in the AVL with inorder traversal. • Collect all above functions under a user menu. Load your HW-9 to FTP site until 14 May. 07 at 09:00 am.

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