Design and Analysis of Algorithms
Price: 1030.00 INR
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ISBN:
9789354977886
Publication date:
30/11/2023
Paperback
Price: 1030.00 INR
We sell our titles through other companies
Disclaimer :You will be redirected to a third party website.The sole responsibility of supplies, condition of the product, availability of stock, date of delivery, mode of payment will be as promised by the said third party only. Prices and specifications may vary from the OUP India site.
ISBN:
9789354977886
Publication date:
30/11/2023
Paperback
The second edition of Design and Analysis of Algorithms is an essential textbook for undergraduate and postgraduate students in computer science and information technology. This book is useful for other engineering branch students who opt for algorithms courses, diploma students and postgraduate students in computer applications. The book is also useful for competitive examinations like GATE and useful for coding interviews. Its primary goal is to equip students with comprehensive knowledge of fundamental concepts related to algorithm design, analysis and implementation aspects of algorithms.
Rights: World Rights
Description
The second edition of Design and Analysis of Algorithms is an essential textbook for undergraduate and postgraduate students in computer science and information technology. This book is useful for other engineering branch students who opt for algorithms courses, diploma students and postgraduate students in computer applications. The book is also useful for competitive examinations like GATE and useful for coding interviews. Its primary goal is to equip students with comprehensive knowledge of fundamental concepts related to algorithm design, analysis and implementation aspects of algorithms.
The book begins with exploring algorithm basics and problem-solving concepts and then introduces topics like algorithm writing and analyses iterative and recursive algorithms. It provides detailed explanations and design techniques, including brute force, divide-and-conquer, decrease-and-conquer, greedy approach, transform-and-conquer, dynamic programming, branch-and-bound, backtracking and Iterative development. Moreover, the book delves into string algorithms, data structures, linear programming, computability theory, NP-hard problems, NP-completeness, randomized algorithms, approximation algorithms, and parallel algorithms, offering a well-rounded and comprehensive coverage of essential topics.
The book includes various chapter-end pedagogical features such as point-wise summary, glossary, review questions, exercises, crosswords and additional problems to help readers test their understanding and apply and practice the concepts learnt. Appendices on basic mathematics and proof techniques are given to aid students in refreshing the fundamental concepts.
Table of contents
- Introduction to Algorithms
- Basics of Algorithm Writing
- Basics of Algorithm Analysis
- Mathematical Analysis of Recursive Algorithms
- Data Structures—I
- Data Structures—II
- Brute Force Approaches
- Divide-and-conquer Approach
- Decrease-and-conquer Approach
- Time–Space Tradeoffs
- Greedy Algorithms
- Transform-and-conquer Approach
- Dynamic Programming
- Backtracking
- Branch-and-bound Technique
- String Algorithms
- Iterative Improvement and Linear Programming
- Basics of Computational Complexity
- Randomized Algorithms
- Approximation Algorithms
- Parallel Algorithms
Features
- In-depth treatment for topics such as Divide and conquer, greedy approach, dynamic programming, transform-and-conquer technique, decrease-and-conquer technique, linear programming, and randomized and approximation algorithms
- Extensive discussion on computational skills, algorithm writing and analysis of iterative and recursive algorithms
- Extensive discussion on the developing and designing aspects of algorithms using minimal mathematics
- Many numerous examples to assist understanding of the concepts
- Judicious presentation of algorithms using a step-wise approach throughout the text
- Historical notes on various topics and chapter-end crossword puzzles provided to engage readers and enhance their interest in the subject
Description
The second edition of Design and Analysis of Algorithms is an essential textbook for undergraduate and postgraduate students in computer science and information technology. This book is useful for other engineering branch students who opt for algorithms courses, diploma students and postgraduate students in computer applications. The book is also useful for competitive examinations like GATE and useful for coding interviews. Its primary goal is to equip students with comprehensive knowledge of fundamental concepts related to algorithm design, analysis and implementation aspects of algorithms.
The book begins with exploring algorithm basics and problem-solving concepts and then introduces topics like algorithm writing and analyses iterative and recursive algorithms. It provides detailed explanations and design techniques, including brute force, divide-and-conquer, decrease-and-conquer, greedy approach, transform-and-conquer, dynamic programming, branch-and-bound, backtracking and Iterative development. Moreover, the book delves into string algorithms, data structures, linear programming, computability theory, NP-hard problems, NP-completeness, randomized algorithms, approximation algorithms, and parallel algorithms, offering a well-rounded and comprehensive coverage of essential topics.
The book includes various chapter-end pedagogical features such as point-wise summary, glossary, review questions, exercises, crosswords and additional problems to help readers test their understanding and apply and practice the concepts learnt. Appendices on basic mathematics and proof techniques are given to aid students in refreshing the fundamental concepts.
Read More
Table of contents
- Introduction to Algorithms
- Basics of Algorithm Writing
- Basics of Algorithm Analysis
- Mathematical Analysis of Recursive Algorithms
- Data Structures—I
- Data Structures—II
- Brute Force Approaches
- Divide-and-conquer Approach
- Decrease-and-conquer Approach
- Time–Space Tradeoffs
- Greedy Algorithms
- Transform-and-conquer Approach
- Dynamic Programming
- Backtracking
- Branch-and-bound Technique
- String Algorithms
- Iterative Improvement and Linear Programming
- Basics of Computational Complexity
- Randomized Algorithms
- Approximation Algorithms
- Parallel Algorithms
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