Best Books for Reading about Data Structure
Data structure books help to comprehend how data structures are the base for abstract data types. Abstract data types form the logical side of data type, and the data structures deal with the physical side. Different types of data structures manage varied applications. Yet some complete specific tasks. The common ones include B-tree indexes that aid relational databases for data retrieval. The compiler applications use hash tables for identifiers. Data structures manage large portions of data, as in internet indexing services or large databases. It can retrieve data from the primary and secondary memory.
Below is a list of books that will help readers better understand data structures. These are must-reads if you want to expand your knowledge on a subject or learn more about it for your career.
10 Must-Read Data Structures Books
Here is a helpful list of books that professionals and beginners can use to improve their understanding of data structures.
|
Sr.no |
Book | Author | Publish Date |
Rating |
| 1 | Introduction to Algorithms | Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein | 1989 | Amazon: 4.6
Goodreads: 4.34 |
| 2 | Algorithms | Robert Sedgewick and Kevin Wayne | 2011 | Amazon: 4.7
Goodreads: 4.41 |
| 3 | Data Structures and Algorithms | Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser | 2014 | Amazon: 4.3
Goodreads: 3.85 |
| 4 | Problem-Solving with Algorithms and Data Structures Using Python | Bradley N. Miller | 2006 | Amazon: 4.6
Goodreads: 4.09 |
| 5 | Data Structures and Algorithms Made Easy: Data Structure and Algorithmic Puzzles | Narasimha Karumanchi | 2016 | Amazon: 4.4
Goodreads: 4.50 |
| 6 | Data Structures and Algorithms in Python | Roberto Tamassia, Michael H. Goldwasser, Michael T. Goodrich | 2013 | Amazon: 4.3
Goodreads: 4.15 |
| 7 | Open Data Structures: An Introduction | Pat Morin | 2013 | Amazon: 4.3
Goodreads: 3.88 |
| 8 | The Algorithm Design Manual | Steven S. Skiena | 2020 | Amazon: 4.5
Goodreads: 4.35 |
| 9 | Data Structures and Algorithms | Alfred Aho | 1982 | Amazon: 4.3
Goodreads: 3.92 |
| 10 | Data Structures and Algorithms in C++ | Adam Drozdek | 2012 | Amazon: 4.3
Goodreads: 3.85 |
Let us discuss the reviews and Keypoints of the Data Structures Books:-
Book #1: Introduction to Algorithms
Author: Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
Review:
The comprehensive book on algorithms covers a wide range of topics, including data structures, sorting algorithms, graph algorithms, and algorithms for computational geometry. Computer science advanced undergraduate or graduate students commonly use this book due to its rigorous approach and comprehensive explanations.
Key Points:
- The book provides a comprehensive algorithm design and analysis foundation.
- This resource comprehensively covers various topics such as data structures, sorting algorithms, graph algorithms, and computational geometry algorithms.
- Computer science students in their advanced undergraduate or graduate years will find this book valuable for its rigorous approach and detailed explanations.
Book #2: Algorithms
Author: Robert Sedgewick and Kevin Wayne
Review:
“Algorithms” is another book that provides a modern treatment of the subject. The book covers various algorithms and data structures and presents them clearly and concisely. The author has kept undergraduates and graduates in mind while compiling the publication. It includes real-world examples and interactive content.
Key Points
- “Algorithms” has a companion website, algs4.cs.princeton.edu
- The book provides an online summary of each section, and the readers get complete Java implementations along with testing data.
- The website offers exercises, answers, engaging visualizations, and lecture slides.
- Readers can avail of the assignments with checklists and links to related material.
Book #3: Data Structures and Algorithms in Java
Author: Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser
Review:
This book focuses on designing and implementing data structures and algorithms in the Java programming language. It covers many topics, including basic data structures (such as lists, stacks, and queues), advanced data structures (such as trees and graphs), and algorithms for sorting, searching, and graph processing. This book is perfect for advanced undergraduate or graduate computer science students. It is renowned for its easy-to-understand explanations and utilization of Java code examples.
Key Points:
- The book focuses on data-structures design, implementation, and algorithms in Java.
- The author has covered primary and advanced data structures with sorting, searching, and graph processing algorithms.
- The content includes clear explanations and the use of Java code examples.
Book #4: Problem-Solving with Algorithms and Data Structures Using Python
Author: Bradley N. Miller and David L. Ranum
Review:
The textbook covers computer science, Python, algorithms, and data structures. It increments from the fundamentals of data structures to complex problem-solving. The author has explained Data structures and algorithms so efficiently that beginners delve into the topic and professionals use it practically.
Key Points:
- The book is helpful for Data scientists in communicating efficiently with software developers.
- The book contains principal data structures and algorithms implemented in Python with real code examples.
- There are plenty of practice problems for the user to grasp data structures and algorithms.
- It is a great reference book for data scientists.
Book #5: Data Structures and Algorithms Made Easy: Data Structure and Algorithmic Puzzles
Author: Narasimha Karumanchi
Review:
The book overviews data structures and algorithms, focusing on problem-solving. It covers topics such as lists, stacks, queues, trees, and graphs and presents them in the context of solving algorithmic puzzles. Advanced undergraduate or graduate computer science students will find this book ideal. Its effective use of examples and clear explanations make it stand out. The book is best for beginners and professionals.
Key Points:
- The book comprehensively covers data structures and algorithms and focuses on problem-solving.
- It covers topics like lists, stacks, queues, trees, and graphs, presenting them in the context of solving algorithmic puzzles.
- The content contains clear explanations with the use of examples.
Book #6: Data Structures and Algorithms in Python
Author: Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser
Review:
The book discusses designing and implementing data structures and algorithms in the Python programming language. It covers many topics, including basic data structures (such as lists, stacks, and queues), advanced data structures (such as trees and graphs), and algorithms for sorting, searching, and graph processing. This book would be perfect for computer science students in their advanced undergraduate or graduate studies. It is excellent because it offers easy-to-understand explanations and practical Python code examples.
Key Points:
- The reader learns how to design and implement data structures and algorithms in Python.
- The book is suitable for advanced undergraduate or graduate students in computer science.
- Clear explanations and the use of Python code examples are the highlights.
Book #7: Problem-Solving with Algorithms and Data Structures Using Python
Author: Pat Morin
Review:
The book offers a rich blend of content from basics to intricate data structures and algorithms. It covers how to sequence or list data structures, ordered and unordered dictionaries, and graphs. Morin has supported the instruction with source code making it easy for readers to comprehend.
Key Points:
- The book covers intricacies like queues and priority queues.
- The fast and efficient approach to data structure includes vigorous mathematics making it easy to understand.
- The book is suitable for beginners and enthusiasts.
Book #8: The Algorithm Design Manual
Author: Steven S. Skiena
Review:
“The Algorithm Design Manual” is a book that provides an overview of algorithm design and analysis, focusing on providing practical guidance for solving real-world problems. It comprises topics including basic data structures, algorithms for sorting and searching, and techniques for designing efficient algorithms. This publication is particularly well-suited for advanced learners pursuing a computer science degree at the undergraduate or graduate level. It is widely recognized for its lucid elucidations and practical illustrations.
Key Points:
- The book is a practical guide for solving real-world problems.
- Users reap a strong understanding of algorithm design and analysis.
- Users can apply this knowledge to solve practical problems.
Book #9: Data Structures and Algorithms
Author: Alfred Aho
Review:
The author has produced a book in Pascal addressing abstract data types. The author unifies Data structures and algorithms for a better understanding with varied implementations. The book covers various algorithm techniques and analyses of fundamental algorithms.
Key Points:
- The author has explored the data structures through Pascal.
- The book is for computer science data structures enthusiasts.
- Users learn to use the array to store sequential elements in data structures.
Book #10: Data Structures and Algorithms in C++
Author: Adam Drozdek
Review
The reader can form a strong foundation with data structures and algorithms to design, execute, and maintain software systems. Users can further their skills in C++ as they learn to put the data structures to use. They enhance their skills in object-oriented paradigms.
Key Points
- Users learn advanced topics such as treaps, k-d trees, and k-d B-trees.
- Readers practically enhance their skills in generational garbage collection.
- The content includes ample C++ code examples.
Recommended Books
Our IT readers can choose from the top 10 recommended books on Data Structures that we have compiled. For a broader range of options, EDUCBA suggests the following.
