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Efficient Algorithm Design

You're reading from   Efficient Algorithm Design Unlock the power of algorithms to optimize computer programming

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781835886823
Length 360 pages
Edition 1st Edition
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Author (1):
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Masoud Makrehchi Masoud Makrehchi
Author Profile Icon Masoud Makrehchi
Masoud Makrehchi
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Foundations of Algorithm Analysis
2. Chapter 1: Introduction to Algorithm Analysis FREE CHAPTER 3. Chapter 2: Mathematical Induction and Loop Invariant for Algorithm Correctness 4. Chapter 3: Rate of Growth for Complexity Analysis 5. Chapter 4: Recursion and Recurrence Functions 6. Chapter 5: Solving Recurrence Functions 7. Part 2: Deep Dive in Algorithms
8. Chapter 6: Sorting Algorithms 9. Chapter 7: Search Algorithms 10. Chapter 8: Symbiotic Relationship between Sort and Search 11. Chapter 9: Randomized Algorithms 12. Chapter 10: Dynamic Programming 13. Part 3: Fundamental Data Structures
14. Chapter 11: Landscape of Data Structures 15. Chapter 12: Linear Data Structures 16. Chapter 13: Non-Linear Data Structures 17. Part 4: Next Steps
18. Chapter 14: Tomorrow’s Algorithms 19. Index 20. Other Books You May Enjoy

Non-deterministic algorithms

Non-deterministic algorithms are theoretical constructs used primarily in the study of computational complexity. They assume the existence of a “non-deterministic” machine, such as a non-deterministic Turing machine, which can make arbitrary choices to explore different computational paths simultaneously. Non-deterministic algorithms are often used to define classes of problems, such as nondeterministic polynomial time (NP), which includes problems for which a solution can be verified in polynomial time by a deterministic algorithm. Non-deterministic algorithms are not practically implementable on standard deterministic machines. They serve as a way to understand the potential power of parallel computation and to classify problem complexity.

Note

Non-deterministic algorithms are not practically implementable on standard deterministic machines. Randomized algorithms, on the other hand, are practical algorithms that use random numbers...

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