Unit 1 (9Hrs) Trees. Mahesh Sanghavi & Deepali Pawar Department of Computer Engineering, SNJB s KBJ College of Engineering, Chandwad, India
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1 Unit 1 (9Hrs) Trees Mahesh Sanghavi & Deepali Pawar Department of Computer Engineering, SNJB s KBJ College of Engineering, Chandwad, India The class notes are a compilation and edition from many sources. The instructor does not claim intellectual property or ownership of the lecture notes.
2 Syllabus Tree- basic terminology, General tree and its representation, representation using sequential and linked organization, Binary tree- properties, converting tree to binary tree, binary tree traversals- inorder, preorder, post order, level wise -depth first and breadth first, Operations on binary tree. Binary Search Tree (BST), BST operations, Threaded binary tree- concepts, threading, insertion and deletion of nodes in inorder threaded binary tree, in order traversal of in-order threaded binary tree. Case Study- Use of binary tree in expression tree-evaluation and Huffman's coding
3 Nature View of a Tree leaves branches root
4 Computer Scientist s View root leaves branches nodes
5 What is a Tree A tree is a finite nonempty set of elements. It is an abstract model of a hierarchical structure. Computers R Us consists of nodes with a parent-child relation. Applications: Organization charts File systems Programming environments US Sales International Manufacturing Laptops Desktops R&D Europe Asia Canada
6 Tree Terminology Root: node without parent (A) Siblings: nodes share the same parent Subtree: tree consisting of a node and its descendants Internal node: node with at least one child (A, B, C, F) External node (leaf ): node without children (E, I, J, K, G, H, D) A Ancestors of a node: parent, grandparent, grand-grandparent, etc. Descendant of a node: child, grandchild, grand-grandchild, etc. B C D Depth of a node: number of ancestors Height of a tree: maximum depth of any node (3) E F G H Degree of a node: the number of its children Degree of a tree: the maximum number of its node. I J K subtree
7 Introduction (3/8) Some Terminology node: the item of information plus the branches to each node. degree: the number of subtrees of a node degree of a tree: the maximum of the degree of the nodes in the tree. terminal nodes (or leaf): nodes that have degree zero nonterminal nodes: nodes that don t belong to terminal nodes. children: the roots of the subtrees of a node X are the children of X parent: X is the parent of its children.
8 Introduction (4/8) Some Terminology (cont d) siblings: children of the same parent are said to be siblings. Ancestors of a node: all the nodes along the path from the root to that node. The level of a node: defined by letting the root be at level one. If a node is at level l, then it children are at level l+1. Height (or depth): the maximum level of any node in the tree
9 Introduction (5/8) Example A is the root node Property: (# edges) = (#nodes) - 1 B is the parent of D and E C is the sibling of B D and E are the children of B D, E, F, G, I are external nodes, or leaves A, B, C, H are internal nodes The level of E is 3 The height (depth) of the tree is 4 A The degree of node B is 2 The degree of the node C is 3 The ancestors of node I is A, C, H The descendants of node C is F, G, H, I B C Level 1 2 D E F G H I 3 4
10 Tree ADT We use positions to abstract nodes Generic methods: integer size() boolean isempty() objectiterator elements() positioniterator positions() Accessor methods: position root() position parent(p) positioniterator children(p) Query methods: boolean isinternal(p) boolean isexternal(p) boolean isroot(p) Update methods: swapelements(p, q) object replaceelement(p, o) Additional update methods may be defined by data structures implementing the Tree ADT
11 Intuitive Representation of Tree Node List Representation ( A ( B ( E ( K, L ), F ), C ( G ), D ( H ( M ), I, J ) ) ) The root comes first, followed by a list of links to sub-trees How many link fields are needed in such a representation? Data Link 1 Link 2 Link n
12 Trees Every tree node: object useful information children pointers to its children Data Data Data Data Data Data Data
13 A Tree Representation A node is represented by an object storing Element Parent node Sequence of children nodes B B A D F A D F C E C E
14 Left Child, Right Sibling Representation Left Child Data Right Sibling A B C D E F G H I J K L
15 Tree Traversal Two main methods: Preorder Postorder Recursive definition Preorder: visit the root traverse in preorder the children (subtrees) Postorder traverse in postorder the children (subtrees) visit the root
16 Preorder Traversal A traversal visits the nodes of a tree in a systematic manner In a preorder traversal, a node is visited before its descendants Application: print a structured document Algorithm preorder(v) visit(v) for each child w of v preorder (w) 1 Become Rich 2 1. Motivations 2. Methods 3. Success Stories Enjoy Life Help Poor Friends 2.1 Get a CS PhD 2.2 Start a Web Site 2.3 Acquired by Google
17 Postorder Traversal In a postorder traversal, a node is visited after its descendants Application: compute space used by files in a directory and its subdirectories Algorithm postorder(v) for each child w of v postorder (w) visit(v) 9 cs16/ 3 homeworks/ 7 programs/ 8 todo.txt 1K h1c.doc 3K h1nc.doc 2K DDR.java 10K Stocks.java 25K Robot.java 20K
18 Binary Tree A binary tree is a tree with the following properties: Each internal node has at most two children (degree of two) The children of a node are an ordered pair We call the children of an internal node left child and right child Applications: arithmetic expressions decision processes searching A Alternative recursive definition: a binary tree is either a tree consisting of a single node, OR a tree whose root has an ordered pair of children, each of which is a binary tree D B E F C G H I
19 BinaryTree ADT The BinaryTree ADT extends the Tree ADT, i.e., it inherits all the methods of the Tree ADT Additional methods: position leftchild(p) position rightchild(p) position sibling(p) Update methods may be defined by data structures implementing the BinaryTree ADT
20 Examples of the Binary Tree Skewed Binary Tree Complete Binary Tree A A 1 A B B 2 B C D C 3 D E F G E 5 4 H I
21 Differences Between A Tree and A Binary Tree The subtrees of a binary tree are ordered; those of a tree are not ordered. A A B B Are different when viewed as binary trees. Are the same when viewed as trees.
22 Data Structure for Binary Trees A node is represented by an object storing Element Parent node Left child node Right child node B B A D A D C E C E
23 Arithmetic Expression Tree Binary tree associated with an arithmetic expression internal nodes: operators external nodes: operands Example: arithmetic expression tree for the expression (2 (a - 1) + (3 b)) a 1 3 b
24 Decision Tree Binary tree associated with a decision process internal nodes: questions with yes/no answer external nodes: decisions Example: dining decision Yes Want a fast meal? No How about coffee? On expense account? Yes No Yes No Starbucks Spike s Al Forno Café Paragon
25 Maximum Number of Nodes in a Binary Tree The maximum number of nodes on depth i of a binary tree is 2 i, i>=0. The maximum nubmer of nodes in a binary tree of height k is 2 k+1-1, k>=0. Prove by induction. k i 0 2 i 2 k + 1-1
26 Full Binary Tree A full binary tree of a given height k has 2 k+1 1 nodes. Height 3 full binary tree.
27 Labeling Nodes In A Full Binary Tree Label the nodes 1 through 2 k+1 1. Label by levels from top to bottom. Within a level, label from left to right
28 Node Number Properties Parent of node i is node i / 2, unless i = 1. Node 1 is the root and has no parent.
29 Node Number Properties Left child of node i is node 2i, unless 2i > n, where n is the number of nodes. If 2i > n, node i has no left child.
30 Node Number Properties Right child of node i is node 2i+1, unless 2i+1 > n, where n is the number of nodes. If 2i+1 > n, node i has no right child.
31 Complete Binary Trees A labeled binary tree containing the labels 1 to n with root 1, branches leading to nodes labeled 2 and 3, branches from these leading to 4, 5 and 6, 7, respectively, and so on. A binary tree with n nodes and level k is complete iff its nodes correspond to the nodes numbered from 1 to n in the full binary tree of level k Complete binary tree Full binary tree of depth 3
32 Binary Tree Traversals Let l, R, and r stand for moving left, visiting the node, and moving right. There are six possible combinations of traversal lrr, lrr, Rlr, Rrl, rrl, rlr Adopt convention that we traverse left before right, only 3 traversals remain lrr, lrr, Rlr inorder, postorder, preorder
33 Inorder Traversal In an inorder traversal a node is visited after its left subtree and before its right subtree 2 6 Algorithm inorder(v) if isinternal (v) inorder (leftchild (v)) visit(v) if isinternal (v) inorder (rightchild (v))
34 Print Arithmetic Expressions Specialization of an inorder traversal print operand or operator when visiting node print ( before traversing left subtree print ) after traversing right subtree + Algorithm inorder (v) if isinternal (v){ print( ( ) inorder (leftchild (v))} print(v.element ()) if isinternal (v){ inorder (rightchild (v)) print ( ) )} 2 - a 1 3 b ((2 (a - 1)) + (3 b))
35 Evaluate Arithmetic Expressions recursive method returning the value of a subtree when visiting an internal node, combine the values of the subtrees + Algorithm evalexpr(v) if isexternal (v) return v.element () else x evalexpr(leftchild (v)) y evalexpr(rightchild (v)) operator stored at v return x y
36 Creativity: pathlength(tree) = depth(v) v tree Algorithm pathlength(v, n) Input: a tree node v and an initial value n Output: the pathlength of the tree with root v Usage: pl = pathlength(root, 0); if isexternal (v) return n return (pathlength(leftchild (v), n + 1) + pathlength(rightchild (v), n + 1) + n)
37 Euler Tour Traversal Generic traversal of a binary tree Includes a special cases the preorder, postorder and inorder traversals Walk around the tree and visit each node three times: on the left (preorder) from below (inorder) on the right (postorder) + L R 2 B
38 Euler Tour Traversal eulertour(node v) { perform action for visiting node on the left; if v is internal then eulertour(v->left); perform action for visiting node from below; if v is internal then eulertour(v->right); perform action for visiting node on the right; }
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