CSCS-200 Data Structure and Algorithms Lecture-19-20.

CSCS-200 Data Structure and Algorithms Lecture-19-20

2 Level-order Traversal There is yet another way of traversing a binary tree that is not related to recursive traversal procedures discussed previously. In level-order traversal, we visit the nodes at each level before proceeding to the next level. At each level, we visit the nodes in a left- to-right order.

3 Level-order Traversal Level-order: 14 4 15 3 9 18 7 16 20 5 17 144 9 7 3 5 15 18 1620 17

4 Level-order Traversal How do we do level-order traversal? Surprisingly, if we use a queue instead of a stack, we can visit the nodes in level- order. Here is the code for level-order traversal:

5  Level-order Traversal void levelorder(TreeNode * treeNode) { Queue * > q; if( treeNode == NULL ) return; q.enqueue( treeNode); while( !q.empty() ) { treeNode = q.dequeue(); cout getInfo()) << " "; if(treeNode->getLeft() != NULL ) q.enqueue( treeNode->getLeft()); if(treeNode->getRight() != NULL ) q.enqueue( treeNode->getRight()); } cout << endl; }

13 Level-order Traversal Queue: 14 Output: 14 497351518162017

14 Level-order Traversal Queue: 4 15 Output: 14 14 4 9735 15 18162017

15 Level-order Traversal Queue: 15 3 9 Output: 14 4 14 4 9 7 3 5 15 18162017

16 Level-order Traversal Queue: 3 9 18 Output: 14 4 15 14 4 9 7 3 5 15 18 1620 17

Level-order Traversal Queue: 9 18 Output: 14 4 15 3 14 4 9 7 3 5 15 18 1620 17

18 Level-order Traversal Queue: 18 7 Output: 14 4 15 3 9 14 4 9 7 3 5 15 18 1620 17

19 Level-order Traversal Queue: 7 16 20 Output: 14 4 15 3 9 18 14 4 9 7 3 5 15 18 1620 17

20 Level-order Traversal Queue: 16 20 5 Output: 14 4 15 3 9 18 7 14 4 9 7 3 5 15 18 1620 17

21 Level-order Traversal Queue: 20 5 17 Output: 14 4 15 3 9 18 7 16 14 4 9 7 3 5 15 18 1620 17

22 Level-order Traversal Queue: 5 17 Output: 14 4 15 3 9 18 7 16 20 14 4 9 7 3 5 15 18 1620 17

23 Level-order Traversal Queue: 17 Output: 14 4 15 3 9 18 7 16 20 5 14 4 9 7 3 5 15 18 1620 17

24 Level-order Traversal Queue: Output: 14 4 15 3 9 18 7 16 20 5 17 14 4 9 7 3 5 15 18 1620 17

25 Storing other Type of Data The examples of binary trees so far have been storing integer data in the tree node. This is surely not a requirement. Any type of data can be stored in a tree node. Here, for example, is the C++ code to build a tree with character strings.

26  Binary Search Tree with Strings void wordTree() { TreeNode * root = new TreeNode (); static char* word[] = "babble", "fable", "jacket", "backup", "eagle","daily","gain","bandit","abandon", "abash","accuse","economy","adhere","advise","cease", "debunk","feeder","genius","fetch","chain", NULL}; root->setInfo( word[0] ); for(i=1; word[i]; i++ ) insert(root, word[i] ); inorder( root ); cout << endl; }

31  Binary Search Tree with Strings void insert(TreeNode * root, char* info) { TreeNode * node = new TreeNode (info); TreeNode *p, *q; p = q = root; while( strcmp(info, p->getInfo()) != 0 && q != NULL ) { p = q; if( strcmp(info, p->getInfo()) < 0 ) q = p->getLeft(); else q = p->getRight(); }

36  Binary Search Tree with Strings if( strcmp(info, p->getInfo()) == 0 ){ cout << "attempt to insert duplicate: " << *info << endl; delete node; } else if( strcmp(info, p->getInfo()) < 0 ) p->setLeft( node ); else p->setRight( node ); }

39 Binary Search Tree with Strings Output: abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket

40 Binary Search Tree with Strings abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket  Notice that the words are sorted in increasing order when we traversed the tree in inorder manner.

41 Binary Search Tree with Strings abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket  Notice that the words are sorted in increasing order when we traversed the tree in inorder manner.  This should not come as a surprise if you consider how we built the BST.

42 Binary Search Tree with Strings abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket  Notice that the words are sorted in increasing order when we traversed the tree in inorder manner.  This should not come as a surprise if you consider how we built the BST.  For a given node, values less than the info in the node were all in the left subtree and values greater or equal were in the right.

43 Binary Search Tree with Strings abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket  Notice that the words are sorted in increasing order when we traversed the tree in inorder manner.  This should not come as a surprise if you consider how we built the BST.  For a given node, values less than the info in the node were all in the left subtree and values greater or equal were in the right.  Inorder prints the left subtree, then the node finally the right subtree.

44 Binary Search Tree with Strings abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket  Notice that the words are sorted in increasing order when we traversed the tree in inorder manner.  This should not come as a surprise if you consider how we built the BST.  For a given node, values less than the info in the node were all in the left subtree and values greater or equal were in the right.  Inorder prints the left subtree, then the node finally the right subtree.  Building a BST and doing an inorder traversal leads to a sorting algorithm.

45 Binary Search Tree with Strings abandon abash accuse adhere advise babble backup bandit cease chain daily debunk eagle economy fable feeder fetch gain genius jacket  Notice that the words are sorted in increasing order when we traversed the tree in inorder manner.  This should not come as a surprise if you consider how we built the BST.  For a given node, values less than the info in the node were all in the left subtree and values greater or equal were in the right.  Inorder prints the left subtree, then the node finally the right subtree.  Building a BST and doing an inorder traversal leads to a sorting algorithm.

46 Deleting a node in BST As is common with many data structures, the hardest operation is deletion. Once we have found the node to be deleted, we need to consider several possibilities. If the node is a leaf, it can be deleted immediately.

47 Deleting a node in BST If the node has one child, the node can be deleted after its parent adjusts a pointer to bypass the node and connect to inorder successor. 6 2 4 3 1 8

48 Deleting a node in BST The inorder traversal order has to be maintained after the delete. 6 2 4 3 1 8 624318 

49 Deleting a node in BST The inorder traversal order has to be maintained after the delete. 6 2 4 3 1 8 62431862318 

50 Deleting a node in BST The complicated case is when the node to be deleted has both left and right subtrees. The strategy is to replace the data of this node with the smallest data of the right subtree and recursively delete that node.

51 Deleting a node in BST Delete(2): locate inorder successor 6253184 Inorder successor

52 Deleting a node in BST Delete(2): locate inorder successor 6253184 Inorder successor  Inorder successor will be the left-most node in the right subtree of 2.  The inorder successor will not have a left child because if it did, that child would be the left-most node.

53 Deleting a node in BST Delete(2): copy data from inorder successor 6253184  6353184

54 Deleting a node in BST Delete(2): remove the inorder successor 6253184  6353184  6353184

55 Deleting a node in BST Delete(2)  635418  6353184

56 C++ code for delete ‘delete’ is C++ keyword. We will call our deleteNode routine remove. Here is the C++ code for remove.

57  C++ code for delete TreeNode * remove(TreeNode * tree, int info) { TreeNode * t; int cmp = info - *(tree->getInfo()); if( cmp < 0 ){ t = remove(tree->getLeft(), info); tree->setLeft( t ); } else if( cmp > 0 ){ t = remove(tree->getRight(), info); tree->setRight( t ); }

61  C++ code for delete //two children, replace with inorder successor else if(tree->getLeft() != NULL && tree->getRight() != NULL ){ TreeNode * minNode; minNode = findMin(tree->getRight()); tree->setInfo( minNode->getInfo() ); t = remove(tree->getRight(), *(minNode->getInfo())); tree->setRight( t ); }

66  C++ code for delete else { // case 1 TreeNode * nodeToDelete = tree; if( tree->getLeft() == NULL ) // will handle 0 children tree = tree->getRight(); else if( tree->getRight() == NULL ) tree = tree->getLeft(); else tree = NULL; delete nodeToDelete; } return tree; }

69  C++ code for delete TreeNode * findMin(TreeNode * tree) { if( tree == NULL ) return NULL; if( tree->getLeft() == NULL ) return tree; // this is it. return findMin( tree->getLeft() ); }

72 BinarySearchTree.h Let us design the BinarySearchTree class (factory).

73  BinarySearchTree.h #ifndef _BINARY_SEARCH_TREE_H_ #define _BINARY_SEARCH_TREE_H_ #include // For NULL // Binary node and forward declaration template class BinarySearchTree;

74  BinarySearchTree.h #ifndef _BINARY_SEARCH_TREE_H_ #define _BINARY_SEARCH_TREE_H_ #include // For NULL // Binary node and forward declaration template class BinarySearchTree;

75  BinarySearchTree.h template class BinaryNode { EType element; BinaryNode *left; BinaryNode *right; BinaryNode( const EType & theElement, BinaryNode *lt, BinaryNode *rt ) : element( theElement ), left( lt ), right( rt ) { } friend class BinarySearchTree ; };

79 BinarySearchTree.h template class BinarySearchTree { public: BinarySearchTree( const EType& notFound ); BinarySearchTree( const BinarySearchTree& rhs ); ~BinarySearchTree( ); const EType& findMin( ) const; const EType& findMax( ) const; const EType& find( const EType & x ) const; bool isEmpty( ) const; void printInorder( ) const;

80 BinarySearchTree.h void insert( const EType& x ); void remove( const EType& x ); const BinarySearchTree & operator= ( const BinarySearchTree & rhs );

81 BinarySearchTree.h private: BinaryNode * root; // ITEM_NOT_FOUND object used to signal failed finds const EType ITEM_NOT_FOUND; const EType& elementAt( BinaryNode * t ); void insert(const EType& x, BinaryNode * & t); void remove(const EType& x, BinaryNode * & t); BinaryNode * findMin(BinaryNode * t); BinaryNode * findMax(BinaryNode * t); BinaryNode * find(const EType& x, BinaryNode * t ); void makeEmpty(BinaryNode * & t); void printInorder(BinaryNode * t); }; #endif

CSCS-200 Data Structure and Algorithms Lecture-19-20.

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