#### 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.
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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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# 9.3 Backtracking

Backtracking is a very useful algorithmic technique that can solve a wide range of complex problems in a reasonable amount of time. It is commonly used in decision-making problems where the set of potential choices can be organized into a decision tree or graph.

The basic idea behind backtracking is to construct a solution one step at a time while checking to see if each step contributes to the overall solution. If a step does not contribute to the solution, it is removed, and the next step is attempted.

One great example of a problem that can be solved using backtracking is the N-Queens puzzle. This puzzle requires the placement of N queens on an NxN chessboard in such a way that no two queens threaten each other. This means that no two queens can be in the same row, column, or diagonal. By using backtracking, it is possible to find a solution to this problem.

Backtracking can also be used in other types of problems, such as finding the shortest path in a maze or...