 # Chapter 19 Implementing Trees and Priority Queues Fundamentals of Java.

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Chapter 19 Implementing Trees and Priority Queues Fundamentals of Java

2 Objectives Use the appropriate terminology to describe trees. Distinguish different types of hierarchical collections such as general trees, binary trees, binary search trees, and heaps.

Fundamentals of Java 3 Objectives (cont.) Understand the basic tree traversals. Use binary search trees to implement sorted sets and sorted maps. Use heaps to implement priority queues.

Fundamentals of Java 4 Vocabulary Binary search tree Binary tree Expression tree General tree Heap Heap property

Fundamentals of Java 5 Vocabulary (cont.) Interior node Leaf Left subtree Parse tree Right subtree Root

Fundamentals of Java 6 An Overview of Trees Tree: Data structure in which each item can have multiple successors – All items have exactly one predecessor. Except a privileged item called the root Parse tree: Describes the syntactic structure of a sentence in terms of its component parts – Noun phrases and verb phrases

Fundamentals of Java 7 An Overview of Trees (cont.) Figure 19-1: Parse tree for a sentence

Fundamentals of Java 8 An Overview of Trees (cont.) Table 19-1: Summary of terms used to describe trees

Fundamentals of Java 9 An Overview of Trees (cont.) Table 19-1: Summary of terms used to describe trees (cont.)

Fundamentals of Java 10 An Overview of Trees (cont.) Figure 19-2: Tree and some of its properties

Fundamentals of Java 11 An Overview of Trees (cont.) General trees: Trees with no restrictions on number of children Binary trees: Each node has at most two children: left child and right child. Figure 19-3: Two unequal binary trees that have equal sets of nodes

Fundamentals of Java 12 An Overview of Trees (cont.) Recursive processing of trees is common, so useful to have recursive definitions of trees – General tree: Either empty or consists of a finite set of nodes T Node r is the root. Set T - {r} partitioned into disjoint subsets (general trees) – Binary tree: Either empty or consists of a root plus a left subtree and a right subtree (binary trees)

Fundamentals of Java 13 An Overview of Trees (cont.) Figure 19-4: Different types of binary trees

Fundamentals of Java 14 An Overview of Trees (cont.) Full binary tree: Contains maximum number of nodes for its height – Fully balanced – If height is d, 2 d -1 nodes – Level n has up to 2 n nodes. – Height of a fully balanced tree of n nodes is log 2 n.

Fundamentals of Java 15 An Overview of Trees (cont.) Heap: Binary tree in which the item in each node is less than or equal to the items in both of its children – Heap property Figure 19-5: Examples of heaps

Fundamentals of Java 16 An Overview of Trees (cont.) Expression tree: For evaluating expressions Figure 19-6: Some expression trees

Fundamentals of Java 17 An Overview of Trees: Binary Search Trees Figure 19-7: Call tree for the binary search of an array

Fundamentals of Java 18 An Overview of Trees: Binary Search Trees (cont.) Figure 19-8: Binary search tree

Fundamentals of Java 19 An Overview of Trees: Binary Search Trees (cont.) Binary search tree: Each node is greater than or equal to left child and less than or equal to right child. Recursive search process:

Fundamentals of Java 20 An Overview of Trees: Binary Search Trees (cont.) Figure 19-9: Three binary tree shapes with the same data

Liang, Introduction to Java Programming, Seventh Edition, (c) 2009 Pearson Education, Inc. All rights reserved. 0136012671 21 Tree Traversal Tree traversal is the process of visiting each node in the tree exactly once. There are several ways to traverse a tree. This section presents inorder, preorder, postorder, depth- first, and breadth-first traversals. The inorder traversal is to visit the left subtree of the current node first, then the current node itself, and finally the right subtree of the current node. The postorder traversal is to visit the left subtree of the current node first, then the right subtree of the current node, and finally the current node itself.

Liang, Introduction to Java Programming, Seventh Edition, (c) 2009 Pearson Education, Inc. All rights reserved. 0136012671 22 Tree Traversal, cont. The preorder traversal is to visit the current node first, then the left subtree of the current node, and finally the right subtree of the current node.

Fundamentals of Java 23 Binary Tree Traversals Figure 19-11: Inorder traversal Figure 19-10: Preorder traversal

Fundamentals of Java 24 Binary Tree Traversals (cont.) Figure 19-13: Level-order traversal Figure 19-12: Postorder traversal

Fundamentals of Java 25 Linked Implementation of Binary Trees Table 19-2: Methods of the BSTPT interface

Fundamentals of Java 26 Linked Implementation of Binary Trees (cont.) Table 19-2: Methods of the BSTPT interface (cont.)

Fundamentals of Java 27 Linked Implementation of Binary Trees (cont.) Figure 19-14: Interfaces and classes used in the binary search tree prototype

Fundamentals of Java 28 Linked Implementation of Binary Trees (cont.) Example 19.1: Interface for binary search tree prototypes

Fundamentals of Java 29 Linked Implementation of Binary Trees (cont.) Example 19.1: Interface for binary search tree prototypes (cont.)

Liang, Introduction to Java Programming, Seventh Edition, (c) 2009 Pearson Education, Inc. All rights reserved. 0136012671 Draw the binary search tree after inserting the following: F 15, 20, 10, 9, 13, 25 30

Liang, Introduction to Java Programming, Seventh Edition, (c) 2009 Pearson Education, Inc. All rights reserved. 0136012671 Draw the binary search tree after inserting the following: F 9, 10, 13,15, 20, 25 31

Fundamentals of Java 32 Linked Implementation of Binary Trees (cont.) add method

Fundamentals of Java 33 Linked Implementation of Binary Trees (cont.) add method (cont.)

Fundamentals of Java 34 Linked Implementation of Binary Trees (cont.) Pseudocode for searching a binary tree:

Fundamentals of Java 35 Linked Implementation of Binary Trees (cont.) Inorder traversal code:

Fundamentals of Java 36 Linked Implementation of Binary Trees (cont.) Pseudocode for level-order traversal:

Fundamentals of Java 37 Linked Implementation of Binary Trees (cont.) Steps for removing a node:

Fundamentals of Java 38 Linked Implementation of Binary Trees (cont.) Expanded step 4 for removing a node from a binary tree:

Fundamentals of Java 39 Array Implementation of a Binary Tree Figure 19-16: Complete binary tree Figure 19-17: Array representation of a complete binary tree

Fundamentals of Java 40 Array Implementation of a Binary Tree (cont.) Table 19-3: Locations of given items in an array representation of a complete binary tree

Fundamentals of Java 41 Array Implementation of a Binary Tree (cont.) Table 19-4: Relatives of a given item in an array representation of a complete binary tree

Fundamentals of Java 42 Implementing Heaps Table 19-5: Methods in the interface HeapPT

Fundamentals of Java 43 Implementing Heaps (cont.) add method:

Fundamentals of Java 44 Implementing Heaps (cont.) pop method:

Fundamentals of Java 45 Implement Heaps (cont.) pop method (cont.):

Fundamentals of Java 46 Using a Heap to Implement a Priority Queue Example 19.3: Heap implementation of a priority queue

Fundamentals of Java 47 Using a Heap to Implement a Priority Queue (cont.) Example 19.3: Heap implementation of a priority queue (cont.)

Fundamentals of Java 48 Summary There are various types of trees or hierarchical collections such as general trees, binary trees, binary search trees, and heaps. The terminology used to describe hierarchical collections is borrowed from biology, genealogy, and geology.

Fundamentals of Java 49 Summary (cont.) Tree traversals: preorder, inorder, postorder, and level-order traversal A binary search tree preserves a natural ordering among its items and can support operations that run in logarithmic time. Binary search trees are useful for implementing sorted sets and sorted maps.

Fundamentals of Java 50 Summary (cont.) Heap – Useful for ordering items according to priority – Guarantees logarithmic insertions and removals – Useful for implementing priority queues Binary search trees typically have a linked implementation. Heaps typically have an array representation.

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