1. Introduction to Algorithms

Author : Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein

This internationally acclaimed textbook provides a comprehensive introduction to the modern study of computer algorithms. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively selfcontained and presents an algorithm, a design technique, an application area, or a related topic. The algorithms are described and designed in a manner to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

Buy from Amazon

2. Algorithms Unlocked

Author : Thomas H. Cormen

For anyone who has ever wondered how computers solve problems, an engagingly written guide for nonexperts to the basics of computer algorithms. Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves into your GPS, your laptop, or your smart phone? This book offers an engagingly written guide to the basics of computer algorithms. In Algorithms Unlocked, Thomas Cormen-coauthor of the leading college textbook on the subject-provides a general explanation, with limited mathematics, of how algorithms enable computers to solve problems. Readers will learn what computer algorithms are, how to describe them, and how to evaluate them.

3. The Algorithm Design Manual

Author : Steven S Skiena

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.

The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography.

4. Data Structures and Algorithms Made Easy

Author : Narasimha Karumanchi

"Data structures and algorithms made easy: data structures and algorithmic puzzles" Is a book that offers solutions to complex data structures and algorithms. There are multiple solutions for each problem and the book is coded in C/C++, it comes handy as an interview and exam guide for computer scientists.

A handy guide of sorts for any computer Science professional, data structures and algorithms made easy: data structures and algorithmic puzzles is a solution Bank for various complex problems related to data structures and algorithms. It can be used as a reference manual by those readers in the computer Science industry. This book serves as guide to prepare for interviews, exams, and campus work. In short, this book offers solutions to various complex data structures and algorithmic problems.

5. Algorithms, Fourth Edition

Author : Robert Sedgewick, Kevin Wayne

This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is one of the most popular textbooks on algorithms today and is widely used in colleges and universities worldwide. The algorithms in this book — including 50 algorithms every programmer should know — represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering and for students who use computation in the liberal arts. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.

6. Data Structures and Algorithms Made Easy in Java

Author : Narasimha Karumanchi

A handy guide of sorts for any computer science professional, Data Structures and Algorithms Made Easy in Java: Data Structure And Algorithmic Puzzles is a solution bank for various complex problems related to data structures and algorithms. It can be used as a reference manual by those readers in the computer science industry.

The book has around 21 chapters and covers Recursion and Backtracking, Linked Lists, Stacks, Queues,Trees, Priority Queue and Heaps, Disjoint Sets ADT, Graph Algorithms, Sorting, Searching, Selection Algorithms [Medians], Symbol Tables, Hashing, String Algorithms, Algorithms Design Techniques, Greedy Algorithms, Divide and Conquer Algorithms, Dynamic Programming, Complexity Classes, and other Miscellaneous Concepts.

7. Analysis and Design of Algorithms

Author : Amrinder Arora

Analysis and Design of Algorithms provides a structured view of algorithm design techniques in a concise, easy-to-read manner. The book was written with an express purpose of being easy - to understand, read, and carry. It presents a pioneering approach in the teaching of algorithms, based on learning algorithm design techniques, and not merely solving a collection of problems. This allows students to master one design technique at a time and apply it to a rich variety of problems. Analysis and Design of Algorithms covers the algorithmic design techniques of divide and conquer, greedy, dynamic programming, branch and bound, and graph traversal. For each of these techniques, there are templates and guidelines on when to use and not to use each technique. Many sections contain innovative mnemonics to aid the readers in remembering the templates and key takeaways. Additionally, the book covers NP-completeness and the inherent hardness of problems. The third edition includes a new section on polynomial multiplication, as well as additional exercise problems, and an updated appendix. Written with input from students and professionals, Analysis and Design of Algorithms is well suited for introductory algorithm courses at the undergraduate and graduate levels. The structured organization of the text makes it especially appropriate for online and distance learning.

8. Conceptual Data Modeling and Database Design: A Fully Algorithmic Approach

Author : Christian Mancas

This new book aims to provide to both beginners and experts with a completely algorithmic approach to data analysis and conceptual modeling, database design, implementation, and tuning, starting from vague and incomplete customer requests and ending with IBM DB/2, Oracle, MySQL, MS SQL Server, or Access based software applications. A rich panoply of solutions to actual useful data sub-universes (e.g. business, university, public and home library, geography, history, etc.) is provided, constituting a powerful library of examples. The book provides a library of useful solutions to real-life problems and provides valuable knowledge on data analysis and modeling, database design, implementation, and fine tuning.

9. Parameterized Algorithms

Author : Marek Cygan, Fedor V. Fomin, Łukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, Saket Saurabh

This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way.

The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds.

10. Algorithm Challenges

Author : Martin Puryear

This book takes the novice programmer into the basics of algorithms and data structures, through intermediate areas such as sorting, before touching upon more advanced topics such as self-balancing trees and graph