Trees and Graphs

Module 8: Trees and Graphs Theme 1: Basic Properties of Trees A (rooted) tree is a finite set of nodes such that ¯ there is a specially designated node called the root. ¯ d Ì ;Ì ;::: ;Ì ½ ¾ the remaining nodes are partitioned into disjoint sets d such that each of these Ì ;Ì ;::: ;Ì d ½ ¾ sets is a tree. The sets d are called subtrees,and the degree of the root. The above is an example of a recursive definition, as we have already seen in previous modules. A Ì Ì Ì B C ¾ ¿ Example 1: In Figure 1 we show a tree rooted at with three subtrees ½ , and rooted at , and D , respectively. We now introduce some terminology for trees: ¯ A tree consists of nodes or vertices that store information and often are labeled by a number or a letter. In Figure 1 the nodes are labeled as A;B;:::;Å. ¯ An edge is an unordered pair of nodes (usually denoted as a segment connecting two nodes). A; B µ For example, ´ is an edge in Figure 1. A ¯ The number of subtrees of a node is called its degree. For example, node is of degree three, while node E is of degree two. The maximum degree of all nodes is called the degree of the tree. Ã ; Ä; F ; G; Å ; Á Â ¯ A leaf or a terminal node is a node of degree zero. Nodes and are leaves in Figure 1. B ¯ A node that is not a leaf is called an interior node or an internal node (e.g., see nodes and D ). X X X ¯ Roots of subtrees of a node are called children of while is known as the parent of its D A A B; C D children. For example, B; C and are children of , while is the parent of and . B; C; D Ã Ä ¯ Children of the same parent are called siblings. Thus are siblings as well as and are siblings. ¯ The ancestors of a node are all the nodes along the path from the root to that node. For example, À; D A ancestors of Å are and . ¯ The descendants of a node are all the nodes along the path from that node to a terminal node. F; E ; Ã Ä Thus descendants of B are and . 1 A T3 T T2 1 B C D E F G H I J K L M Figure 1: Example of a tree. 1 Ð ¯ The level of a node is defined by letting the root to be at level zero , while a node at level has ·½ A B; C; D children at level Ð . For example, the root in Figure 1 is at level zero, nodes are Ã ; Ä; Å at level one, nodes E ; F ; G; À ; Á ; Â ate level two, and nodes are at level three. ¯ The depth of a node is its level number. The height of a tree is the maximum level of any Å node in this tree. Node G is at depth two, while node at depth three. The height of the tree presented in Figure 1 is three. d d ¯ A tree is called a -ary tree if every internal node has no more than children. A tree is called d a full d-ary tree if every internal node has exactly children. A complete tree isafulltreeup the last but one level, that is, the last level of such a tree is not full. A binary tree is a tree with =¾ ¿ d . The tree in Figure 1 is a -ary tree, which is neither a full tree nor a complete tree. ¯ An ordered rooted tree is a rooted tree where the children of each internal node are ordered. We usually order the subtrees from left to right. Therefore, for a binary (ordered) tree the subtrees are called the left subtree and the right subtree. ¯ A forest is a set of disjoint trees. Now we study some basic properties of trees. We start with a simple one. Ò ½ Theorem 1. A tree with Ò nodes has edges. ½ Proof. Every node except the root has exactly one in-coming edge. Since there are Ò nodes other ½ than the root, there are Ò edges in a tree. 1Some authors prefer to set the root to be on level one. 2 The next result summarizes our basic knowledge about the maximum number of nodes and the height. Theorem 2. Let us consider a binary tree. i ¾ i ¼ (i) The maximum number of nodes at level i is for . h·½ ¾ ½ (ii) The maximum number of all nodes in a tree of height h is . Ò (iii) If a binary tree of height h has nodes then h ÐÓg ´Ò ·½µ ½: ¾ Ð (iv) If a binary tree of height h has leaves, then h ÐÓg Ð: ¾ =¼ Proof. We first proof (i) by induction. It is easy to see that it is true for i since there is only one i node (the root) at level zero. Let now, by the induction hypothesis, assume there are no more ¾ nodes i·½ i ·½ ¾ at level i. We must prove that at level there are no more than nodes. Indeed, every node i ¾ i at level i may have no more than two children. Since there are nodes on level ,wemusthaveno i i·½ ¡ ¾=¾ i ·½ more than ¾ nodes at level . By mathematical induction we prove (i). To prove (ii) we use (i) and the summation formula for the geometric progression. Since every i h level has at most ¾ nodes and there are no more than levels the total number of nodes cannot exceed h X i h·½ ¾ =¾ ½; i=¼ which proves (ii). h·½ ¾ ½ Now we prove (iii). If a tree has height h, then the maximum number of nodes by (ii) is which must be at least be as big as Ò,thatis, h·½ ¾ ½ Ò: ÐÓg ´Ò ·½µ ½ This implies that h , and completes the proof of (iii). Part (iv) can be proved in ¾ exactly the same manner (see also Theorem 3 below). d k Exercise 8A: Consider a d- ary tree (i.e., nodes have degree at most ). Show that at level there are k h·½ h ´d ½µ=´d ½µ at most d nodes. Conclude the total number of nodes in a tree of height is . Finally, we prove one result concerning a relationship between the number of leaves and the number of nodes of higher degrees. 3 A B D C E F Figure 2: Illustration to Theorem 3. Ò Ò ¾ Theorem 3. Let us consider a nonempty binary tree with ¼ leaves and nodes of degree two. Then Ò = Ò ·½: ¼ ¾ Ò Ò Proof.Let be the total number of all nodes, and ½ the number of nodes of degree one. Clearly Ò = Ò · Ò · Ò : ¼ ½ ¾ On the other hand, if b is the number of edges, then — as already observed in Theorem 1 — we have = b ·½ Ò . But also Ò = b ·½ = Ò ·¾Ò ·½ ½ ¾ Comparing the last two displayed equations we prove out theorem. Ò =¾ Ò =½ Ò =¿ Ò = Ò ·½ ½ ¼ ¼ ¾ In Figure 2 the reader can verify that ¾ , and , hence as predicted by Theorem 3. Theme 2: Tree Traversals Trees are often used to store information. In order to retrieve such information we need a procedure to visit all nodes of a tree. We describe here three such procedures called inorder, postorder and preorder traversals. Throughout this section we assume that trees are ordered trees (from left to right). Ì Ì ;Ì ;::: Ì ½ ¾ Definition.Let be an (ordered) rooted tree with d subtrees of the root. Ì 1. If Ì is null, then the empty list is preorder, inorder and postorder traversal of . Ì 2. If Ì consists of a single node, then that node is preorder, inorder and postorder traversal of . Ì ;Ì ;::: Ì ½ ¾ 3. Otherwise, let d be nonempty subtrees of the root. 4 start end T1 T2 T3 T1 T2 T3 T1 T2 T3 end start pre-order in-order post-order Figure 3: Illustration to preorder, inorder and postorder traversals. Ì Ì ¯ The preorder traversal of nodes in is the following: the root of followed by the Ì Ì ::: Ì ½ ¾ nodes of in preorder, then nodes of in preorder traversal, , followed by d in preorder (cf. Figure 3). ¯ Ì Ì The inorder traversal of nodes in is the following: nodes of ½ in inorder, followed Ì Ì ;Ì ;::: ;Ì ¾ ¿ by the root of , followed by the nodes of d in inorder (cf. Figure 3). ¯ Ì Ì The postorder traversal of nodes in is the following: nodes of ½ in postorder, fol- Ì ;::: ;Ì ¾ lowed by d in postorder, followed by the root (cf. Figure 3). Ì A Ì B Ì ¾ Example 2: Let us consider the tree in Figure 1. The root has three subtrees ½ rooted at , C Ì D rooted at , and subtree ¿ rooted at .Thepreorder traversal is fA; B ; E ; Ã ; Ä; F ; C ; G; D ; À ; Å ; Á ; Â g preorder of T = A Ì B Ì Ì ½ ¾ since after the root we visit first ½ (so we list the root and visit subtrees of ), then subtree C Ì D rooted at and its subtrees, and finally we visit the subtree ¿ rooted and its subtrees. The inorder traversal of Ì is fÃ ; E ; Ä; B ; F ; A; G; C ; Å ; À ; D ; Á ; Â g inorder of T = Ì B Ì ¾ since we first must traverse inorder the subtree ½ rooted at . But inorder traversal of starts by Ã Ã traversing in inorder the subtree rooted at E , which in turn must start at .Since is a single node, we list it. Then we move backward and list the root, which is E , and move to the right subtree that B A turns out to be a single node Ä.

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