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Efficient Algorithm Design

Efficient Algorithm Design

By : Masoud Makrehchi
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Efficient Algorithm Design

Efficient Algorithm Design

By: Masoud Makrehchi

Overview of this book

Efficient Algorithm Design redefines algorithms, tracing the evolution of computer science as a discipline bridging natural science and mathematics. Author Masoud Makrehchi, PhD, with his extensive experience in delivering publications and presentations, explores the duality of computers as mortal hardware and immortal algorithms. The book guides you through essential aspects of algorithm design and analysis, including proving correctness and the importance of repetition and loops. This groundwork sets the stage for exploring algorithm complexity, with practical exercises in design and analysis using sorting and search as examples. Each chapter delves into critical topics such as recursion and dynamic programming, reinforced with practical examples and exercises that link theory with real-world applications. What sets this book apart is its focus on the practical application of algorithm design and analysis, equipping you to solve real programming challenges effectively. By the end of this book, you’ll have a deep understanding of algorithmic foundations and gain proficiency in designing efficient algorithms, empowering you to develop more robust and optimized software solutions.
Table of Contents (21 chapters)
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1
Part 1: Foundations of Algorithm Analysis
7
Part 2: Deep Dive in Algorithms
13
Part 3: Fundamental Data Structures
17
Part 4: Next Steps

Queue

A queue operates on the FIFO principle, meaning it has a behavior opposite to stacks: The first element added is the first to be removed. This structure is analogous to a line of people waiting for service: The first person in line is the first to be served. Queues are used in various scenarios, including task scheduling, buffering, and managing resources in computer systems.

Queues have several characteristics that influence their behavior and performance:

  • FIFO order: The first element inserted into the queue is the first one to be removed.
  • Operations at opposite ends: Elements are added at the rear (end) of the queue and removed from the front (beginning) of the queue.
  • Dynamic size: Queues can dynamically grow or shrink as elements are enqueued or dequeued. As we enqueue more elements, the size of the queue increases, and as we dequeue elements, the size decreases.
  • No random access: Like stacks and unlike arrays, we cannot directly access elements at...
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Efficient Algorithm Design
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