Book Image

C++ Data Structures and Algorithms

By : Wisnu Anggoro
5 (1)
Book Image

C++ Data Structures and Algorithms

5 (1)
By: Wisnu Anggoro

Overview of this book

C++ is a general-purpose programming language which has evolved over the years and is used to develop software for many different sectors. This book will be your companion as it takes you through implementing classic data structures and algorithms to help you get up and running as a confident C++ programmer. We begin with an introduction to C++ data structures and algorithms while also covering essential language constructs. Next, we will see how to store data using linked lists, arrays, stacks, and queues. Then, we will learn how to implement different sorting algorithms, such as quick sort and heap sort. Along with these, we will dive into searching algorithms such as linear search, binary search and more. Our next mission will be to attain high performance by implementing algorithms to string datatypes and implementing hash structures in algorithm design. We'll also analyze Brute Force algorithms, Greedy algorithms, and more. By the end of the book, you'll know how to build components that are easy to understand, debug, and use in different applications.

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Table of Contents (16 chapters)
Title Page
Title Page
Copyright and Credits
Copyright and Credits
Packt Upsell
Packt Upsell
Contributors
Contributors
Preface
Preface
Free Chapter
1
Learning Data Structures and Algorithms in C++
Learning Data Structures and Algorithms in C++
Technical requirements
Introduction to basic C++
Developing abstract data types
Analyzing the algorithm
Summary
QA section
Further reading
2
Storing Data in Lists and Linked Lists
Storing Data in Lists and Linked Lists
Technical requirements
Getting closer to an array
Building a List ADT
Introduction to node
Building a Singly Linked List ADT
Building the Doubly Linked List ADT
Applying List and LinkedList using STL
Summary
QA section
Further reading
3
Constructing Stacks and Queues
Constructing Stacks and Queues
Technical requirements
Building a Stack ADT
Building a Queue ADT
Building a Deque ADT
Summary
QA section
Further reading
4
Arranging Data Elements Using a Sorting Algorithm
Arranging Data Elements Using a Sorting Algorithm
Technical requirements
Bubble sort
Selection sort
Insertion sort
Merge sort
Quick sort
Counting sort
Radix sort
Summary
QA section
Further reading
5
Finding out an Element Using Searching Algorithms
Finding out an Element Using Searching Algorithms
Technical requirements
Linear search
Binary search
Ternary search
Interpolation search
Jump search
Exponential search
Sublist search
Summary
QA section
Further reading
6
Dealing with the String Data Type
Dealing with the String Data Type
Technical requirement
String in C++
Playing with words
Constructing a string from binary digits
Subsequence string
Pattern searching
Summary
QA section
Further reading
7
Building a Hierarchical Tree Structure
Building a Hierarchical Tree Structure
Technical requirements
Building a binary tree ADT
Building a binary search tree ADT
Building a balanced BST (AVL) ADT
Building a binary heap ADT
Summary
QA section
Further reading
8
Associating a Value to a Key in a Hash Table
Associating a Value to a Key in a Hash Table
Technical requirement
Getting acquainted with hash tables
Implementing a separate chaining technique
Implementing the open addressing technique
Summary
QA section
Further reading
9
Implementation of Algorithms in Real Life
Implementation of Algorithms in Real Life
Technical requirements
Greedy algorithms
Divide and conquer algorithms
Dynamic programming
Brute-force algorithms
Randomized algorithms
Backtracking algorithms
Summary
QA section
Further reading
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Index
Index

Building a binary search tree ADT

A binary search tree (BST) is a sorted binary tree, where we can easily search for any key using the binary search algorithm. To sort the BST, it has to have the following properties:

  • The node's left subtree contains only a key that's smaller than the node's key
  • The node's right subtree contains only a key that's greater than the node's key
  • You cannot duplicate the node's key value

By having the preceding properties, we can easily search for a key value as well as find the maximum or minimum key value. Suppose we have the following BST:

As we can see in the preceding tree diagram, it has been sorted since all of the keys in the root's left subtree are smaller than the root's key, and all of the keys in the root's right subtree are greater than the root's key. The preceding BST is a balanced BST since it has a balanced left and right subtree. We also can define the preceding BST as a balanced BST since both the left and right subtrees have an equal height (we...

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