STARTING OUT WITH C++ MPL
9th Edition
ISBN: 9780136673989
Author: GADDIS
Publisher: PEARSON
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Chapter 19.2, Problem 19.12CP
Program Plan Intro
Operations that are performed on Binary search tree:
Binary search tree performs various operations such as:
- Creating a binary tree
- Inserting nodes
- Finding nodes
- Deleting nodes
Leaf node:
Binary tree is similar to an upside down tree. It structure is anchored at the top by using a tree pointer that resembles the header pointer of the standard linked list.
- The first node that is present in the tree is called as root node. Every root node will have pointer to other nodes namely child nodes. Child nodes are also referenced using pointers.
- When a node does not contain any child node is called as leaf node.
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Chapter 19 Solutions
STARTING OUT WITH C++ MPL
Ch. 19.1 - Prob. 19.1CPCh. 19.1 - Prob. 19.2CPCh. 19.1 - Prob. 19.3CPCh. 19.1 - Prob. 19.4CPCh. 19.1 - Prob. 19.5CPCh. 19.1 - Prob. 19.6CPCh. 19.2 - Prob. 19.7CPCh. 19.2 - Prob. 19.8CPCh. 19.2 - Prob. 19.9CPCh. 19.2 - Prob. 19.10CP
Ch. 19.2 - Prob. 19.11CPCh. 19.2 - Prob. 19.12CPCh. 19 - Prob. 1RQECh. 19 - Prob. 2RQECh. 19 - Prob. 3RQECh. 19 - Prob. 4RQECh. 19 - Prob. 5RQECh. 19 - Prob. 6RQECh. 19 - Prob. 7RQECh. 19 - Prob. 8RQECh. 19 - Prob. 9RQECh. 19 - Prob. 10RQECh. 19 - Prob. 11RQECh. 19 - Prob. 12RQECh. 19 - Prob. 13RQECh. 19 - Prob. 14RQECh. 19 - Prob. 15RQECh. 19 - Prob. 16RQECh. 19 - Prob. 17RQECh. 19 - Prob. 18RQECh. 19 - Prob. 19RQECh. 19 - Prob. 20RQECh. 19 - Prob. 1PCCh. 19 - Prob. 2PCCh. 19 - Prob. 3PCCh. 19 - Prob. 4PCCh. 19 - Prob. 5PCCh. 19 - Prob. 6PCCh. 19 - Prob. 7PCCh. 19 - Prob. 8PCCh. 19 - Prob. 9PCCh. 19 - Prob. 10PC
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- Change the following code for Depth First Search Strategy so that the graph (graph values in dictionary) generates randomly. # Using a Python dictionary to act as an adjacency listgraph = { '5' : ['3','7'], '3' : ['2', '4'], '7' : ['8'], '2' : [], '4' : ['8'], '8' : []} visited = set() # Set to keep track of visited nodes of graph. def dfs(visited, graph, node): #function for dfs if node not in visited: print (node) visited.add(node) for neighbour in graph[node]: dfs(visited, graph, neighbour) # Driver Codeprint("Following is the Depth-First Search")dfs(visited, graph, '5')arrow_forwardDescribe how to construct a doubly linked list.arrow_forwardWhich of the following points is true about Linked List data structure when it is compared with array: It is easy to insert and delete elements in Linked List. Random access is allowed in a implementation of Linked Lists. Linked list consume less memory than Array. Time complexity for any operation in a linked list is O(1)arrow_forward
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