Best Reference Books – Design and Analysis of Algorithms

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We have compiled the list of Top 10 Best Reference Books on Design and Analysis of Algorithms subject. These books are used by students of top universities, institutes and colleges. Here is the full list of top 10 best books on Design and Analysis of Algorithms along with reviews.

Kindly note that we have put a lot of effort into researching the best books on Design and Analysis of Algorithms subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Design and Analysis of Algorithms" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.

1. “Introduction to Algorithms (Eastern Economy Edition)” by Thomas H Cormen and Charles E Leiserson

“Introduction to Algorithms” Book Review: This text provides an overview and introduction to the contemporary study of computer algorithms. Discusses a wide range of algorithms with design and analysis easily understandable by the reader. Available in 3rd edition, each chapter includes an algorithm, a design technique, an application area or a related topic. Algorithms are simply designed and narrated for those experienced with little programming. The explanations given are rich even though the description is uncomplicated. 2 new chapters on Van Emde Boas trees and Multithreaded Algorithms are included along with considerable insertions to the chapter on Recurrences (now “Divide and Conquer”). It presents treatment of dynamic programming and greedy algorithms in an improvised way and a new idea of edge-based flow in the material on flow networks. Recommended for students and technical professionals in data structures and algorithms. It explores engineering issues in algorithm design and mathematical aspects too. The book is categorized into foundations, sorting and order statistics, data structures, advanced designs and analysis techniques, advanced data structures, graph algorithms, and selected topics as 7 sections. The first section discusses the role of algorithms in computing, analysing and designing algorithms, insertion sort, growth of functions, recurrences, probabilistic analysis and randomized algorithms. The next section discusses heapsort, quicksort, sorting in linear time, and medians and order statistics. Sorting networks, matrix operations, linear programming, polynomials and FFT, number-theoretic algorithms, string matching, computational geometry, and NP completeness. Solved out examples and more problems are given at the end of each chapter. The text ends with an appendix on mathematical background.

2. “Design and Analysis of Computer Algorithms” by AHO

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“The Design and Analysis of Computer Algorithms” Book Review: A textbook that provides foundation on basic data structures and programming techniques frequently used in methodical algorithms. The fundamental concepts of algorithms are explored in this text. The text introduces the reader to models of computation followed by design of efficient algorithms, sorting and order statistics, data structures for set manipulation problems, algorithms on graphs, matrix multiplication and related operations, Fast Fourier Transform and its applications, integer and polynomial arithmetic, pattern matching algorithms, NP complete problems, some provably interactive problems, and lower bounds on numbers of arithmetic. With a bibliography and index, the book ends with much more problems and exercises so that the students can better learn the concepts and better prepare him for exams.

3. “Fundamentals of Computer Algorithms(second edition)” by Sahni Horowitz

“Fundamentals of Data Structures in C” Book Review: This text is more of a reference material for professionals that provides a comprehensive and thorough overview of all forms of data structure implementation in ANSI C. Stacks, queues, lists, search structures, advanced tree structures are some of the concepts discussed in this text. Latest variations of data structure have also found their way in this text which include fibonacci heaps, splay trees, red-black trees, 2-3 trees, 2-3-4 trees, leftist trees, binomial heaps, min-max heaps, and deaps. Written in a comprehensive and student-friendly manner, each chapter ends with solved out algorithms and more questions where the student can test his ability on programming and prepare for the exams.

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4. “Introduction to the Design and Analysis of Algorithms” by Anany Levitin

“Introduction to the Design and Analysis of Algorithms” Book Review: This text is for those interested more in learning algorithms and it is based on a new categorization of algorithm design techniques and a comprehensible portrayal of analysis methods. It provides a thorough understanding of the concepts in the introduction before providing a fixed study of each technique. The book starts with a basic introduction followed by a study on fundamentals of the analysis of algorithm efficiency. Brute force, divide-and-conquer, decrease-and-conquer, transform-and-conquer, space and time tradeoffs, dynamic programming, greedy technique, iterative improvement, limitations of algorithm power and coping with its limitations are some of the topics discussed broadly. To drive the reader’s interest and to build up their skills in computational solving, popular puzzles are provided. Summary of each chapter, solution manual and hints to the exercises are provided at the finish of each chapter.

5. “Design and Analysis of Algorithms” by S Sridhar

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“Design and Analysis of Algorithms” Book Review: This text is recommended for B.Tech/B.E (CSE/IT), M.Tech/M.E (CSE/IT), MCA, M.Sc (CS/IT). It discusses fundamental concepts on algorithms, framework for algorithm analysis, asymptotic notations, sorting algorithms, recurrences, divide-and-conquer approach, dynamic programming approach, greedy algorithms, graph algorithms, backtracking, string matching, NP completeness, NP-complete problems (with proofs). The text is written in a simple language with attention on sorting algorithms, NP completeness and approximation algorithms. About 250 worked out examples are provided with a reference table for time complexity of algorithms, previous 3 years solved university question papers, short type questions with answers, solved GATE question papers as appendices at the end of this text.

6. “Algorithm Design: Foundations, Analysis and Internet Examples” by Michael T Goodrich and Roberto Tamassia

“Algorithm Design: Foundations, Analysis and Internet Examples” Book Review: A textbook that covers the introduction, design, implementation and analysis of computer algorithms and data structures from the latest point of view. It strikes a balance between theoretical analysis techniques and algorithmic design patterns and experimental methods for algorithm engineering. Classified into 4 units: fundamental tools, graph algorithms, internet algorithmics, and additional topics. The 1st section deals with algorithm analysis, basic data structures, search trees and skip lists, sorting, sets and selection, and fundamental techniques. Graphs, weighted graphs, network flow and matching are the topics discussed in section 2. The section on internet algorithmics discuss text processing, number theory and cryptography, and network algorithms. Computational geometry, NP-completeness, algorithmic frameworks are the additional topics explored with useful mathematical facts, bibliography and an index at the end of the book.

7. “Design and Analysis of Algorithms” by Dave

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“Design and Analysis of Algorithms” Book Review: This text is divided into 2 parts. Part 1 is dedicated to algorithm design whereas Part 2 is dedicated to algorithm analysis. The former discusses problem solving with a computer, top-down design, iterative algorithm design issues, computation models and design by refinement, proof rules – basics, design by proof rules, design using recursion, divide-and-conquer method, greedy method, dynamic programming, backtracking, branch and bound, natural algorithms – GA, ANN, SA, TS. Second part deals with efficiency of algorithms, examples of complexity calculations, time-space trade-off, tractable and non-tractable problems, some NP and NP-complete problems, randomized and approximate algorithms, formal specifications-model oriented and algebraic. The book ends with a bibliography and 5 appendices.

8. “Design And Analysis of Algorithms” by Shewta Bajaj Mundra

“Design and Analysis of Algorithms” Book Review: Written in a simple style, this text is recommended for practising programmers. The book begins with an introduction to algorithms subsequently afterward growth order, elementary data structure, divide-and-conquer strategy, greedy method, dynamic programming, and NP-completeness. Each chapter starts with an overview of it and ends with a summary and few exercises. The text ends with a question bank where the students can easily prepare for exams and understand the lesson better. An appendix and a bibliography with more than 100 citations are also provided.

9. “Introduction to Design and Analysis of Algorithms (Anna University)” by Anany Levitin
10. “An Introduction to Parallel Computing: Design and Analysis of Algorithms” by GRAMA

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“An Introduction to Parallel Computing: Design and Analysis of Algorithms” Book Review: This text provides a basic foundation at the techniques for the design and analysis of parallel algorithms and programming using commercially available platforms. It explores principles of parallel algorithms design and different parallel programming methods MPI, POSIX threads and OpenMP are also studied. The text is divided into 3 sections: basics, parallel programming, parallel algorithms and applications. Parallel programming platforms, principles of parallel algorithm design, analytical modelling of parallel programs, and basic communication operations are the topics discussed in Part 1. Part 2 deals with parallel programming paradigms, programming shared address space platforms, and programming message passing platforms. Part 3 discusses dense matrix algorithms, sorting, graph algorithms, discrete optimization problems, dynamic programming, fast fourier transform, and solving sparse systems of linear equations. Problems are provided at the end of each chapter to work out so that the student can get an understanding of the algorithms.

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Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn | Youtube | Instagram | Facebook | Twitter