How to think about algorithms
By: Edmonds, Jeff.
Publisher: New Delhi Cambridge University Press 2008Description: xiii, 448p.ISBN: 9781107439887.Subject(s): Algorithms-study and teachingDDC classification: 518.1 | Ed56h Summary: This textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Books | PK Kelkar Library, IIT Kanpur | General Stacks | 518.1 Ed56h (Browse shelf) | Available | A184165 |
Browsing PK Kelkar Library, IIT Kanpur Shelves , Collection code: General Stacks Close shelf browser
518.1 Ab88o Optimization algorithms on matrix manifolds | 518.1 D656m Methods in algorithmic analysis | 518.1 D851c Concentration of measure for the analysis of randomized algorithms | 518.1 Ed56h How to think about algorithms | 518.1 G178d Discrete calculus | 518.1 K811a Algorithms for optimization | 518.1 M698P PROBABILITY AND COMPUTING |
This textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.
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