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"101 Algorithms Questions You Must Know" presents 101 asymptotic complexity Questions and Answers, organized by Algorithm Design Techniques. Serving as a useful accompaniment to "Analysis and Design of Algorithms" (ISBN 978-1516513086), the questions are distributed as follows: 9 Warm up Questions on Math Basics, 19 Questions on Asymptotic Analysis and Asymptotic Notation, 3 Questions on Data Structures, 17 Questions on Divide and Conquer, 8 Questions on Greedy Algorithms, 18 Questions on Dynamic Programming, 5 Questions on Graph Traversal (BFS/DFS), 4 Questions on Branch and Bound, 9 Questions on NP-Completeness 3 Questions on Lower Bounds, and 6 Questions on Graph Theory.Covering many questions used by major technology companies as their interview questions, this book serves both software professionals as well as graduate students in the field.
Analysis and Design of Algorithms provides a structured view of algorithm design techniques in a concise, easy-to-read manner. The book was written with an express purpose of being easy - to understand, read, and carry.It presents a pioneering approach in the teaching of algorithms, based on learning algorithm design techniques, and not merely solving a collection of problems. This allows students to master one design technique at a time and apply it to a rich variety of problems.Analysis and Design of Algorithms covers the algorithmic design techniques of divide and conquer, greedy, dynamic programming, branch and bound, and graph traversal. For each of these techniques, there are templates and guidelines on when to use and not to use each technique. Many sections contain innovative mnemonics to aid the readers in remembering the templates and key takeaways. Additionally, the book covers NP-completeness and the inherent hardness of problems. The third edition includes a new section on polynomial multiplication, as well as additional exercise problems, and an updated appendix.Written with input from students and professionals, Analysis and Design of Algorithms is well suited for introductory algorithm courses at the undergraduate and graduate levels. The structured organization of the text makes it especially appropriate for online and distance learning.
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