The Algorithm Design Manual

The Algorithm Design ManualFree Download The Algorithm Design Manual 3rd Edition Book in PDF written by Steven S. Skiena (Department of Computer Science Stony Brook University, Stony Brook, NY, USA) and Published by Springer.

According to the Author, “Many professional programmers are not well prepared to tackle algorithm design problems. This is a pity, because the techniques of algorithm design form one of the core practical technologies of computer science. This book is intended as a manual on algorithm design, providing access to combinatorial algorithm technology for both students and computer professionals. It is divided into two parts: Techniques and Resources. The former is a general introduction to the design and analysis of computer algorithms. The Resources section is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations, and an extensive bibliography.

Equally important is what is not done in this book. I do not stress the mathematical analysis of algorithms, leaving most of the analysis as informal arguments. You will not find a single theorem anywhere in this book. When more details are needed, the reader should study the cited programs or references. The goal of this manual is to get you going in the right direction as quickly as possible.

This book covers enough material for a standard Introduction to Algorithms course. It is assumed that the reader has completed the equivalent of a second programming course, typically titled Data Structures or Computer Science II. A full set of lecture slides for teaching this course are available online at www.algorist.com. Further, I make available online video lectures using these slides to teach a full-semester algorithm course. Let me help teach your course, through the magic of the Internet!

Table of Contents

  1. Introduction to Algorithm Design
  2. Algorithm Analysis
  3. Data Structures
  4. Sorting
  5. Divide and Conquer
  6. Hashing and Randomized Algorithms
  7. Graph Traversal
  8. Weighted Graph Algorithms
  9. Combinatorial Search
  10. Dynamic Programming
  11. NP-Completeness
  12. Dealing with Hard Problems
  13. How to Design Algorithms
  14. Catalog of Algorithmic Problems
  15. Data Structures
  16. Numerical Problems
  17. Combinatorial Problems
  18. Graph Problems: Polynomial Time
  19. Graph Problems: NP-Hard
  20. Computational Geometry
  21. Set and String Problems
  22. Algorithmic Resources
  23. Bibliography

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You may also like to download Introduction to Algorithms Third Edition in PDF

 

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