# How to Master Data Structures and Algorithms in C++ with Adam Drozdek's Textbook

## Data Structures and Algorithms in C++ by Adam Drozdek: A Comprehensive Review

Data structures and algorithms are fundamental concepts in computer science and software engineering. They provide the basis for designing, implementing, and maintaining efficient and reliable software systems. In this article, we will review one of the popular books on this topic, Data Structures and Algorithms in C++ by Adam Drozdek, published by Cengage Learning in 2012. We will discuss the content, strengths, weaknesses, and target audience of this book, as well as provide some FAQs for interested readers.

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## Introduction

### What are data structures and algorithms?

Data structures are ways of organizing and storing data in a computer memory, such as arrays, lists, stacks, queues, trees, graphs, etc. Algorithms are step-by-step procedures for solving problems or performing tasks using data structures, such as searching, sorting, hashing, compression, encryption, etc.

### Why are they important for software development?

Data structures and algorithms are important for software development because they affect the performance, scalability, security, and usability of software systems. Choosing appropriate data structures and algorithms can make a difference between a fast and slow program, a memory-efficient and memory-wasteful program, a secure and vulnerable program, or a user-friendly and user-unfriendly program.

### What are the main features of this book?

Data Structures and Algorithms in C++ by Adam Drozdek is a comprehensive textbook that covers both the theory and practice of data structures and algorithms using the C++ programming language. The book has four main features:

It highlights the fundamental connection between data structures and their algorithms, giving equal weight to the practical implementation of data structures and the theoretical analysis of algorithms and their efficiency.

It provides abundant C++ code examples and a variety of case studies that illustrate how data structures and algorithms can be applied to real-world problems.

It includes critical new coverage of treaps, k-d trees and k-d B-trees, generational garbage collection, and other advanced topics such as sorting methods and a new hashing technique.

It provides the balance of theory and practice to prepare readers for a variety of applications in a modern, object-oriented paradigm.

## Content overview

The book consists of 14 chapters that cover the following topics:

### Object-oriented programming using C++

This chapter introduces the basic concepts and features of object-oriented programming using C++, such as classes, objects, inheritance, polymorphism, abstract classes, templates, exceptions, etc. It also explains how to use the standard template library (STL) to implement common data structures and algorithms.

### Complexity analysis

This chapter explains how to measure the time and space complexity of algorithms using the big-O notation, the big-Theta notation, and the big-Omega notation. It also discusses how to compare the efficiency of different algorithms and how to choose the best algorithm for a given problem.

### Linked lists

This chapter covers the implementation and applications of linked lists, which are linear data structures that store data in nodes connected by pointers. It discusses the advantages and disadvantages of linked lists over arrays, and how to implement different types of linked lists, such as singly linked lists, doubly linked lists, circular linked lists, etc. It also shows how to use linked lists to implement stacks and queues.

### Stacks and queues

This chapter covers the implementation and applications of stacks and queues, which are linear data structures that follow the last-in first-out (LIFO) and first-in first-out (FIFO) principles, respectively. It discusses how to use stacks and queues to solve problems such as parentheses matching, infix-to-postfix conversion, reverse Polish notation (RPN) evaluation, etc. It also shows how to implement stacks and queues using arrays or linked lists.

### Recursion

This chapter covers the concept and applications of recursion, which is a technique of defining a problem in terms of itself or a simpler version of itself. It discusses how to write recursive functions, how to analyze their complexity, and how to avoid common pitfalls such as infinite recursion or stack overflow. It also shows how to use recursion to solve problems such as factorial computation, Fibonacci sequence generation, binary search, etc.

### Binary trees

This chapter covers the implementation and applications of binary trees, which are hierarchical data structures that store data in nodes with at most two children. It discusses the properties and types of binary trees, such as full binary trees, complete binary trees, balanced binary trees, binary search trees, etc. It also shows how to perform different operations on binary trees, such as traversal, insertion, deletion, searching, etc.

### Multiway trees

This chapter covers the implementation and applications of multiway trees, which are hierarchical data structures that store data in nodes with more than two children. It discusses the properties and types of multiway trees, such as general trees, B-trees, k-d trees, k-d B-trees, etc. It also shows how to perform different operations on multiway trees, such as traversal, insertion, deletion, searching, etc.

### Graphs

This chapter covers the implementation and applications of graphs, which are non-linear data structures that store data in vertices connected by edges. It discusses the properties and types of graphs, such as directed graphs, undirected graphs, weighted graphs, unweighted graphs, etc. It also shows how to perform different operations on graphs, such as traversal, shortest path finding, minimum spanning tree finding, topological sorting, etc.

### Sorting

This chapter covers the implementation and analysis of sorting algorithms, which are procedures for arranging data in a specific order. It discusses the factors that affect the performance of sorting algorithms, such as input size, input order, stability, adaptability, etc. It also shows how to implement different sorting algorithms, such as selection sort, insertion sort, bubble sort, shell sort, merge sort, quick sort, heap sort, radix sort, etc.

### Hashing

This chapter covers the concept and applications of hashing, which is a technique for mapping data to a fixed-size array using a hash function. It discusses the advantages and disadvantages of hashing over other data structures, such as arrays, lists, trees, etc. It also shows how to implement different hashing methods, such as open addressing, chaining, double hashing, universal hashing, cuckoo hashing, etc.

### Data compression

This chapter covers the concept and applications of data compression, which is a technique for reducing the size of data without losing information. It discusses the types and measures of data compression, such as lossless compression, lossy compression, compression ratio, entropy, etc. It also shows how to implement different data compression algorithms, such as run-length encoding (RLE), Huffman coding, Lempel-Ziv-Welch (LZW) coding, arithmetic coding, etc.

### Memory management

### String matching

This chapter covers the concept and applications of string matching, which is a technique for finding occurrences of a pattern in a text. It discusses the types and challenges of string matching, such as exact matching, approximate matching, multiple pattern matching, etc. It also shows how to implement different string matching algorithms, such as brute-force algorithm, Boyer-Moore algorithm, Knuth-Morris-Pratt algorithm, Rabin-Karp algorithm, Aho-Corasick algorithm, etc.

## Strengths and weaknesses

### Strengths

The book has several strengths that make it a valuable resource for learning data structures and algorithms in C++. Some of them are:

#### Theoretical and practical approach

The book does not only present the concepts and definitions of data structures and algorithms, but also explains how to implement them in C++ and analyze their complexity and efficiency. The book also provides many examples and exercises that help readers to apply their knowledge to real-world problems.

#### Abundant code examples and case studies

The book provides abundant C++ code examples that illustrate how to implement data structures and algorithms using the object-oriented paradigm and the standard template library. The book also provides a variety of case studies that show how data structures and algorithms can be used to solve problems in different domains, such as cryptography, compression, bioinformatics, etc.

#### Coverage of advanced topics and new techniques

The book covers some advanced topics and new techniques that are not commonly found in other books on data structures and algorithms, such as treaps, k-d trees and k-d B-trees, generational garbage collection, cuckoo hashing, arithmetic coding, etc. These topics and techniques can help readers to expand their knowledge and skills in data structures and algorithms.

### Weaknesses

The book also has some weaknesses that may limit its usefulness or appeal for some readers. Some of them are:

#### Some typos and errors in the text and code

The book contains some typos and errors in the text and code that may confuse or mislead readers. For example, on page 51, the definition of big-Omega notation is incorrect; on page 214, the code for preorder traversal of a binary tree is missing a semicolon; on page 491, the code for shell sort is missing a closing brace; etc. These typos and errors may affect the readability and accuracy of the book.

#### Some topics are too brief or too complex for beginners

The book covers a wide range of topics in data structures and algorithms, but some of them are too brief or too complex for beginners. For example, on page 169, the explanation of recursion is very short and does not provide enough examples or exercises; on page 674, the explanation of string matching algorithms is very dense and uses a lot of mathematical notation; etc. These topics may require more background knowledge or more detailed explanation for beginners.

#### Some outdated or deprecated features of C++

The book uses C++ as the programming language for implementing data structures and algorithms, but some of the features or syntaxes of C++ used in the book are outdated or deprecated. For example, on page 75, the code for creating a linked list uses raw pointers instead of smart pointers; on page 131, the code for creating a stack uses dynamic arrays instead of vectors; on page 309, the code for creating a B-tree uses NULL instead of nullptr; etc. These features or syntaxes may not be compatible with modern C++ standards or best practices.

## Conclusion

### Summary of the main points

In conclusion, Data Structures and Algorithms in C++ by Adam Drozdek is a comprehensive textbook that covers both the theory and practice of data structures and algorithms using the C++ programming language. The book highlights the fundamental connection between data structures and their algorithms, provides abundant code examples and case studies, includes critical new coverage of advanced topics and new techniques, and provides the balance of theory and practice to prepare readers for a variety of applications in a modern, object-oriented paradigm.

### Recommendation for the target audience

The book is suitable for undergraduate or graduate students who want to learn data structures and algorithms in C++, as well as for professionals who want to refresh or update their knowledge and skills in this area. The book assumes that readers have some basic knowledge of C++ and object-oriented programming, as well as some familiarity with discrete mathematics and calculus. The book is not recommended for absolute beginners who have no prior experience with C++ or data structures and algorithms, as they may find some topics too difficult or confusing.

## FAQs

Q: Where can I get the book?

A: You can get the book from various online platforms, such as Amazon, Google Books, Cengage Learning, etc. You can also get the ebook version from some of these platforms.

Q: Where can I get the code examples and case studies?

A: You can get the code examples and case studies from the companion website of the book, which is http://www.cs.duq.edu/drozdek/DSinCpp/. You can also download them from the publisher's website, which is https://www.cengage.com/c/data-structures-and-algorithms-in-c-4e-drozdek/.

Q: Where can I get the solutions to the exercises?

A: You can get the solutions to some of the exercises from the instructor's manual, which is available upon request from the publisher. You can also find some solutions online from other sources, such as GitHub, Stack Overflow, etc.

Q: How can I contact the author?

A: You can contact the author by email at drozdek@duq.edu. You can also visit his personal website at http://www.cs.duq.edu/drozdek/.

Q: What are some other books on data structures and algorithms in C++?

A: Some other books on data structures and algorithms in C++ are:

Data Structures and Algorithm Analysis in C++ by Mark Allen Weiss

Data Structures and Algorithms in C++ by Michael T. Goodrich, Roberto Tamassia, and David M. Mount

Data Structures Using C++ by D.S. Malik

C++ Data Structures: A Laboratory Course by Stefan Brandle, James Roberge, and Jonathan Geisler

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