This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.
| ISBN: | 9783319098876 |
| Publication date: | 15th September 2014 |
| Author: | Dana Vrajitoru, William Knight |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Paperback |
| Pagination: | 466 pages |
| Series: | Undergraduate Topics in Computer Science |
| Genres: |
Algorithms and data structures Mathematical theory of computation Computer programming / software engineering |
This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.
Practical Analysis of Algorithms features in the following genres: Algorithms and data structures, Mathematical theory of computation, Computer programming / software engineering
Practical Analysis of Algorithms is available in Paperback
Practical Analysis of Algorithms was written by Dana Vrajitoru, William Knight and published by Springer an imprint of Springer International Publishing
Practical Analysis of Algorithms has 466 pages
Yes it is part of Undergraduate Topics in Computer Science series