*Data Structure and Algorithmic Puzzles, Second Edition*

**Author**: Narasimha Karumanchi

**Publisher:** N.A

**ISBN:** 9788192107554

**Category:**

**Page:** 438

**View:** 1445

Video Link: youtube.com/watch?v=l_GRquIrVyg 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. Data Structures And Algorithms Made Easy in Java: Data Structure And Algorithmic Puzzles by Narasimha Karumanchi was published in 2011, and it is coded in Java language. This book serves as guide to prepare for interviews, exams, and campus work. It is also available in C/C++. In short, this book offers solutions to various complex data structures and algorithmic problems. Peeling Data Structures and Algorithms for (Java, Second Edition): Programming puzzles for interviewsCampus PreparationDegree/Masters Course PreparationInstructor'sBig job hunters: Microsoft, Google, Apple, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Face book, McAfee and many moreReference Manual for working people What is unique? Our main objective isn't to propose theorems and proofs about DS and Algorithms. We took the direct route and solved problems of varying complexities. That is, each problem corresponds to multiple solutions with different complexities. In other words, we ennumerated possible solutions. With this approach, even when a new question arises, we offer a choice of different solution strategies based on your priorities. Topics Covered: IntroductionRecursion and BacktrackingLinked ListsStacksQueuesTreesPriority Queue and HeapsDisjoint Sets ADTGraph AlgorithmsSorting Searching Selection Algorithms [Medians] Symbol Tables Hashing String Algorithms Algorithms Design Techniques Greedy Algorithms Divide and Conquer Algorithms Dynamic Programming Complexity Classes Miscellaneous Concepts Target Audience? These books prepare readers for interviews, exams, and campus work. Language? All code was written in Java. If you are using C/C++, please search for "Data Structures and Algorithms Made Easy." Also, check out sample chapters and the blog at: CareerMonk.com

Peeling Data Structures and Algorithms for (Java, Second Edition): * Programming puzzles for interviews * Campus Preparation * Degree/Masters Course Preparation * Instructor's * GATE Preparation * Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more * Reference Manual for working people

Provides solutions for approximately 700 algorithmic puzzles--often providing multiple solutions with different complexities. Primarily intended to help programmers prepare for technical job interviews, help students prepare for computer science courses and exams, and serve as a reference manual.

Peeling Data Structures and Algorithms for interviews [re-printed with corrections and new problems]: "Data Structures And Algorithms Made Easy: Data Structure 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 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. Data Structures And Algorithms Made Easy: Data Structure And Algorithmic Puzzles by Narasimha Karumanchi was published in March, and it is coded in C/C++ language. This book serves as guide to prepare for interviews, exams, and campus work. It is also available in Java. In short, this book offers solutions to various complex data structures and algorithmic problems. What is unique? Our main objective isn't to propose theorems and proofs about DS and Algorithms. We took the direct route and solved problems of varying complexities. That is, each problem corresponds to multiple solutions with different complexities. In other words, we enumerated possible solutions. With this approach, even when a new question arises, we offer a choice of different solution strategies based on your priorities. Topics Covered: IntroductionRecursion and BacktrackingLinked ListsStacksQueuesTreesPriority Queue and HeapsDisjoint Sets ADTGraph AlgorithmsSorting Searching Selection Algorithms [Medians] Symbol Tables Hashing String Algorithms Algorithms Design Techniques Greedy Algorithms Divide and Conquer Algorithms Dynamic Programming Complexity Classes Miscellaneous Concepts Target Audience? These books prepare readers for interviews, exams, and campus work. Language? All code was written in C/C++. If you are using Java, please search for "Data Structures and Algorithms Made Easy in Java." Also, check out sample chapters and the blog at: CareerMonk.com

Algorithmic puzzles are puzzles involving well-defined procedures for solving problems. This book will provide an enjoyable and accessible introduction to algorithmic puzzles that will develop the reader's algorithmic thinking. The first part of this book is a tutorial on algorithm design strategies and analysis techniques. Algorithm design strategies — exhaustive search, backtracking, divide-and-conquer and a few others — are general approaches to designing step-by-step instructions for solving problems. Analysis techniques are methods for investigating such procedures to answer questions about the ultimate result of the procedure or how many steps are executed before the procedure stops. The discussion is an elementary level, with puzzle examples, and requires neither programming nor mathematics beyond a secondary school level. Thus, the tutorial provides a gentle and entertaining introduction to main ideas in high-level algorithmic problem solving. The second and main part of the book contains 150 puzzles, from centuries-old classics to newcomers often asked during job interviews at computing, engineering, and financial companies. The puzzles are divided into three groups by their difficulty levels. The first fifty puzzles in the Easier Puzzles section require only middle school mathematics. The sixty puzzle of average difficulty and forty harder puzzles require just high school mathematics plus a few topics such as binary numbers and simple recurrences, which are reviewed in the tutorial. All the puzzles are provided with hints, detailed solutions, and brief comments. The comments deal with the puzzle origins and design or analysis techniques used in the solution. The book should be of interest to puzzle lovers, students and teachers of algorithm courses, and persons expecting to be given puzzles during job interviews.

The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.

Data Structures and Algorithms in Java, Second Edition is designed to be easy to read and understand although the topic itself is complicated. Algorithms are the procedures that software programs use to manipulate data structures. Besides clear and simple example programs, the author includes a workshop as a small demonstration program executable on a Web browser. The programs demonstrate in graphical form what data structures look like and how they operate. In the second edition, the program is rewritten to improve operation and clarify the algorithms, the example programs are revised to work with the latest version of the Java JDK, and questions and exercises will be added at the end of each chapter making the book even more useful. Educational Supplement Suggested solutions to the programming projects found at the end of each chapter are made available to instructors at recognized educational institutions. This educational supplement can be found at www.prenhall.com, in the Instructor Resource Center.

It is the Python version of "Data Structures and Algorithms Made Easy." Table of Contents: goo.gl/VLEUca Sample Chapter: goo.gl/8AEcYk Source Code: goo.gl/L8Xxdt The sample chapter should give you a very good idea of the quality and style of our book. In particular, be sure you are comfortable with the level and with our Python coding style. This book focuses on giving solutions for complex problems in data structures and algorithm. It even provides multiple solutions for a single problem, thus familiarizing readers with different possible approaches to the same problem. "Data Structure and Algorithmic Thinking with Python" is designed to give a jump-start to programmers, job hunters and those who are appearing for exams. All the code in this book are written in Python. It contains many programming puzzles that not only encourage analytical thinking, but also prepares readers for interviews. This book, with its focused and practical approach, can help readers quickly pick up the concepts and techniques for developing efficient and effective solutions to problems. Topics covered include: Organization of Chapters Introduction Recursion and Backtracking Linked Lists Stacks Queues Trees Priority Queues 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 Hacks on Bit-wise Programming Other Programming Questions

"Coding Interview Questions" is a book that presents interview questions in simple and straightforward manner with a clear-cut explanation. This book will provide an introduction to the basics. It comes handy as an interview and exam guide for computer scientists.

Algorithm Design Techniques: Recursion, Backtracking, Greedy, Divide and Conquer, and Dynamic Programming Algorithm Design Techniques is a detailed, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. What's Inside Enumeration of possible solutions for the problems. Performance trade-offs (time and space complexities) between the algorithms. Covers interview questions on data structures and algorithms. All the concepts are discussed in a lucid, easy to understand manner. Interview questions collected from the actual interviews of various software companies will help the students to be successful in their campus interviews. Python-based code samples were given the book.

Now in its second edition, D.S. Malik brings his proven approach to C++ programming to the CS2 course. Clearly written with the student in mind, this text focuses on Data Structures and includes advanced topics in C++ such as Linked Lists and the Standard Template Library (STL). The text features abundant visual diagrams, examples, and extended Programming Examples, all of which serve to illuminate difficult concepts. Complete programming code and clear display of syntax, explanation, and example are used throughout the text, and each chapter concludes with a robust exercise set. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Data Structures and Algorithm Analysis in Java is an “advanced algorithms” book that fits between traditional CS2 and Algorithms Analysis courses. In the old ACM Curriculum Guidelines, this course was known as CS7. This text is for readers who want to learn good programming and algorithm analysis skills simultaneously so that they can develop such programs with the maximum amount of efficiency. Readers should have some knowledge of intermediate programming, including topics as object-based programming and recursion, and some background in discrete math. As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs in Java. Weiss clearly explains topics from binary heaps to sorting to NP-completeness, and dedicates a full chapter to amortized analysis and advanced data structures and their implementation. Figures and examples illustrating successive stages of algorithms contribute to Weiss’ careful, rigorous and in-depth analysis of each type of algorithm. A logical organization of topics and full access to source code complement the text’s coverage.

Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.

Create classic data structures and algorithms such as depth-first search and breadth-first search, learn recursion, as well as create and use a heap data structure using JavaScript Key Features Implement common data structures and the associated algorithms along with the context in which they are used Master existing JavaScript data structures such as arrays, sets, and maps, and learn how to implement new ones such as stacks, linked lists, trees, and graphs in ES 8 Develop abstract data types to make JavaScript a more flexible and powerful programming language Book Description A data structure is a particular way of organizing data in a computer to utilize resources efficiently. Data structures and algorithms are the base of every solution to any programming problem. With this book, you will learn to write complex and powerful code using the latest ES 2017 features. Learning JavaScript Data Structures and Algorithms begins by covering the basics of JavaScript and introduces you to ECMAScript 2017, before gradually moving on to the most important data structures such as arrays, queues, stacks, and linked lists. You will gain in-depth knowledge of how hash tables and set data structures function as well as how trees and hash maps can be used to search files in an HD or represent a database. This book serves as a route to take you deeper into JavaScript. You’ll also get a greater understanding of why and how graphs, one of the most complex data structures, are largely used in GPS navigation systems in social networks. Toward the end of the book, you’ll discover how all the theories presented in this book can be applied to solve real-world problems while working on your own computer networks and Facebook searches. What you will learn Declare, initialize, add, and remove items from arrays, stacks, and queues Create and use linked lists, doubly linked lists, and circular linked lists Store unique elements with hash tables, dictionaries, and sets Explore the use of binary trees and binary search trees Sort data structures using algorithms such as bubble sort, selection sort, insertion sort, merge sort, and quick sort Search elements in data structures using sequential sort and binary search Who this book is for If you’re a JavaScript developer who wants to dive deep into JavaScript and write complex programs using JavaScript data structures and algorithms, this book is for you.

More and more programmers are turning to Python and this book will give them the understanding they need. Necaise introduces the basic array structure and explores the fundamentals of implementing and using multi-dimensional arrays. The underlying mechanisms of many of Python’s built-in data structures and constructs are covered. A number of ADTs and applications are discussed as threads throughout the book to allow for multiple implementations as new data structures are introduced. Real-world applications of the various chapter topics are also presented. This gives programmers complete coverage of abstraction and the basic data structures and algorithms in the Python language.

This new edition provides a comprehensive coverage of fundamental data structures, making it ideal for use in computer science Courses. Real-world applications are a unique feature of this text. Dr. Sahni provides several applications for each data structure and algorithm design method disussed, taking examples from topics such as sorting, compression and coding, and image processing.

Though your application serves its purpose, it might not be a high performer. Learn techniques to accurately predict code efficiency, easily dismiss inefficient solutions, and improve the performance of your application. Key Features Explains in detail different algorithms and data structures with sample problems and Java implementations where appropriate Includes interesting tips and tricks that enable you to efficiently use algorithms and data structures Covers over 20 topics using 15 practical activities and exercises Book Description Learning about data structures and algorithms gives you a better insight on how to solve common programming problems. Most of the problems faced everyday by programmers have been solved, tried, and tested. By knowing how these solutions work, you can ensure that you choose the right tool when you face these problems. This book teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications. What you will learn Understand some of the fundamental concepts behind key algorithms Express space and time complexities using Big O notation. Correctly implement classic sorting algorithms such as merge and quicksort Correctly implement basic and complex data structures Learn about different algorithm design paradigms, such as greedy, divide and conquer, and dynamic programming Apply powerful string matching techniques and optimize your application logic Master graph representations and learn about different graph algorithms Who this book is for If you want to better understand common data structures and algorithms by following code examples in Java and improve your application efficiency, then this is the book for you. It helps to have basic knowledge of Java, mathematics and object-oriented programming techniques.

About The Book: Bruno Preiss presents readers with a modern, object-oriented perspective for looking at data structures and algorithms, clearly showing how to use polymorphism and inheritance, and including fragments from working and tested programs. The book uses a single class hierarchy as a framework to present all of the data structures. This framework clearly shows the relationships between data structures and illustrates how polymorphism and inheritance can be used effectively.

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. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java

Implement classic and functional data structures and algorithms using Python About This Book A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures. Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Who This Book Is For The book will appeal to Python developers. A basic knowledge of Python is expected. What You Will Learn Gain a solid understanding of Python data structures. Build sophisticated data applications. Understand the common programming patterns and algorithms used in Python data science. Write efficient robust code. In Detail Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications. Style and Approach The easy-to-read book with its fast-paced nature will improve the productivity of Python programmers and improve the performance of Python applications.