Art of Algorithm Design

This book provides a comprehensive introduction to algorithms and their programming implementations in C-Language, covering concepts, design principles, and complexities. It serves as a valuable handbook for understanding algorithms and their applications.

\n Format: Hardback
\n Length: 298 pages
\n Publication date: 15 October 2021
\n Publisher: Taylor & Francis Ltd
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Understand the fundamental concepts and design principles of algorithms, encompassing their complexities. Engage in hands-on programming implementations using the C-Language, showcasing practical applications of various algorithms. Serve as an invaluable resource, offering self-explanatory chapters enriched with problems and solutions, empowering readers to excel in algorithm mastery.

Understanding the fundamental concepts and design principles of algorithms is crucial for developing efficient and effective solutions to complex problems. By grasping these concepts, programmers can analyze algorithms' time and space complexity, identify their optimal runtime, and choose the most suitable algorithm for a particular task.

One of the key principles of algorithms is their efficiency, which measures how well they perform in terms of computational resources. Algorithms that are efficient use fewer resources, such as memory and processing power, to solve a problem, making them more suitable for large datasets or real-time applications.

Another important principle is the divide-and-conquer approach, which involves breaking down a complex problem into smaller subproblems that can be solved more easily. This approach is commonly used in sorting algorithms, such as bubble sort and quick sort, as well as in searching algorithms, such as binary search and linear search.

Algorithms also play a critical role in data compression, where they are used to reduce the size of digital data without losing information. Compression algorithms, such as Huffman coding and LZW compression, are used in various applications, including image and video compression, file storage, and network communication.

In addition to these principles, algorithms are designed with specific constraints and requirements in mind. For example, some algorithms may require specific input formats, while others may have limitations on the amount of memory they can use.

To implement algorithms effectively, programmers need to have a solid understanding of programming languages, such as C, C++, Java, or Python. These languages provide the necessary tools and libraries to write and execute algorithms, as well as to analyze their performance and optimize them for different platforms and environments.

In conclusion, understanding the fundamental concepts and design principles of algorithms is essential for developing proficient programmers and solving complex problems efficiently. By grasping these principles, programmers can write effective algorithms, analyze their performance, and optimize them for different platforms and environments.

Demonstrating the programming implementations of all the algorithms using the C-Language is a crucial step in understanding and applying algorithms in real-world scenarios. By writing code in C, programmers can gain a deep understanding of the underlying principles and logic of each algorithm, as well as the challenges and considerations involved in implementing them.

One of the advantages of programming in C is its low-level nature, which allows programmers to have direct control over the hardware and software resources of the system. This level of control enables programmers to optimize algorithms for specific hardware architectures, such as CPUs or GPUs, and to implement them efficiently and with minimal overhead.

Another advantage of programming in C is its portability, which means that code written in C can be compiled and executed on different platforms, including Windows, macOS, Linux, and even embedded systems. This portability allows algorithms to be deployed across a wide range of applications and devices, from smartphones and laptops to industrial control systems and scientific research instruments.

In addition to its low-level nature and portability, C is also a widely used programming language in the software development industry. It is supported by a vast community of developers, including many open-source projects and libraries, which makes it easy to find resources and support for developing algorithms in C.

To demonstrate the programming implementations of all the algorithms using the C-Language, programmers can follow a step-by-step approach. First, they need to select an algorithm that they want to implement. Then, they need to study the algorithm's specifications and requirements, including any input and output formats, time and space complexity, and any special constraints or assumptions.

Once they have a clear understanding of the algorithm, programmers can start writing code in C. They need to pay attention to the syntax, data types, and control structures of the language, as well as any specific libraries or frameworks that may be required for the algorithm.

During the coding process, programmers need to test their code thoroughly to ensure that it is correct and efficient. They can use various testing techniques, such as unit testing and integration testing, to identify and fix any bugs or errors in the code.

Once the code is tested and debugged, programmers can compile it into an executable program and run it on a target platform. They can then analyze the program's performance, including its execution time and memory usage, and make any necessary optimizations to improve its efficiency.

In conclusion, demonstrating the programming implementations of all the algorithms using the C-Language is a valuable skill for any programmer who wants to understand and apply algorithms in real-world scenarios. By writing code in C, programmers can gain a deep understanding of the underlying principles and logic of each algorithm, as well as the challenges and considerations involved in implementing them.

Be an excellent handbook on algorithms with self-explanatory chapters enriched with problems and solutions.

An excellent handbook on algorithms should provide a comprehensive and self-explanatory introduction to the fundamental concepts and design principles of algorithms. It should cover topics such as sorting algorithms, searching algorithms, graph algorithms, and machine learning algorithms, and explain how they work, their advantages, and their limitations.

The handbook should also include detailed programming implementations of all the algorithms using the C-Language. Each chapter should provide step-by-step instructions on how to write and execute code for each algorithm, along with examples and explanations to help readers understand the code and its purpose.

In addition to programming implementations, the handbook should also include a wealth of problems and solutions related to each algorithm. These problems should be designed to test readers' understanding of the concepts and to help them apply the algorithms in real-world scenarios. The solutions should be detailed and easy to follow, and should include any necessary code or explanations.

Furthermore, the handbook should be well-organized and easy to navigate. It should include a table of contents, an index, and a glossary to help readers find the information they need quickly and easily.

To ensure that the handbook is of high quality and meets the needs of its readers, it should be written by experienced algorithms experts and programmers. The authors should have a deep understanding of the subject matter and should be able to communicate complex concepts in a clear and concise manner.

In conclusion, an excellent handbook on algorithms should provide a comprehensive and self-explanatory introduction to the fundamental concepts and design principles of algorithms, along with detailed programming implementations and a wealth of problems and solutions. By following these guidelines, authors can create a valuable resource for programmers and students interested in learning more about algorithms and their applications.

\n Weight: 582g\n
Dimension: 217 x 243 x 23 (mm)\n
ISBN-13: 9780367555115\n \n