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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

Graphs

Graphs are one of the most versatile and widely used non-linear data structures. They are used to represent relationships between entities, where entities are represented as nodes (also called vertices) and relationships as edges. Graphs can model a wide range of real-world problems, from social networks to transportation systems and communication protocols.

Graphs come in various types, each with specific properties that make them suitable for different tasks. Here are the most common types of graphs:

  • Undirected graphs: In undirected graphs, edges have no direction. The relationship between two nodes is bidirectional (see Figure 13.1). If there is an edge between node A and node B, you can traverse from A to B or from B to A without any restrictions. An example of an undirected graph is the social network of Facebook friends, where connections are mutual. This means if A is friends with B, then B is also friends with A, reflecting the bidirectional nature of the...
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83
Tech Concepts
36
Programming languages
73
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Efficient Algorithm Design
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