#### Overview of this book

Begin your journey into the fascinating world of algorithms with this comprehensive course. Starting with an introduction to the basics, you will learn about pseudocode and flowcharts, the fundamental tools for representing algorithms. As you progress, you'll delve into the efficiency of algorithms, understanding how to evaluate and optimize them for better performance. The course will also cover various basic algorithm types, providing a solid foundation for further exploration. You will explore specific categories of algorithms, including search and sort algorithms, which are crucial for managing and retrieving data efficiently. You will also learn about graph algorithms, which are essential for solving problems related to networks and relationships. Additionally, the course will introduce you to the data structures commonly used in algorithms. Towards the end, the focus shifts to algorithm design techniques and their real-world applications. You will discover various strategies for creating efficient and effective algorithms and see how these techniques are applied in real-world scenarios. By the end of the course, you will have a thorough understanding of algorithmic principles and be equipped with the skills to apply them in your technical career.
Table of Contents (14 chapters)
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Chapter 1: Introduction to Algorithms
Chapter 2: Pseudocode and Flowcharts
Chapter 3: Algorithm Efficiency
Chapter 4: Basic Algorithm Types
Chapter 5: Search Algorithms
Chapter 6: Sort Algorithms
Chapter 7: Graph Algorithms
Chapter 8: Data Structures Used in Algorithms
Chapter 9: Algorithm Design Techniques
Chapter 10: Real World Applications of Algorithms
Conclusion
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# 6.5 Merge Sort

Merge sort is a highly efficient and powerful algorithm that is used to sort large datasets. The algorithm follows the divide-and-conquer paradigm, which involves breaking down a problem into smaller sub-problems that are easier to solve. Specifically, Merge sort works by dividing an unsorted list of numbers into two halves and then sorting each half using recursion. After sorting the two halves, the algorithm then merges them back together to create a sorted list.

One of the key advantages of Merge sort over other sorting algorithms is its ability to handle large datasets. Since the algorithm works by dividing the dataset into smaller sub-problems, it can easily be parallelized to run on multiple processors or computers. This makes it an ideal choice for sorting large datasets in distributed systems.

Another advantage of Merge sort is its stability. A sorting algorithm is considered stable if it maintains the relative order of identical elements in the input sequence...