Sam Morley
Learn to break down and solve real-world problems with modern C++ using the proven power of computational thinking.Key Features:- Apply computational thinking to tackle complex C++ challenges- Use abstraction, algorithms, and data structures the C++ way- Build scalable, efficient, and reusable C++ code through real-world projects- Purchase of the print or Kindle book includes a free PDF eBookBook Description:Solve complex problems in C++ by learning how to think like a computer scientist. This book introduces computational thinking-a framework for solving problems using decomposition, abstraction, and pattern recognition-and shows you how to apply it using modern C++ features. You’ll learn how to break down challenges, choose the right abstractions, and build solutions that are both maintainable and efficient.Through small examples and a large case study, this book guides you from foundational concepts to high-performance applications. You’ll explore reusable templates, algorithms, modularity, and even parallel computing and GPU acceleration. With each chapter, you’ll not only expand your C++ skillset, but also refine the way you approach and solve real-world problems.Written by a seasoned research engineer and C++ developer, this book combines practical insight with academic rigor. Whether you’re designing algorithms or profiling production code, this book helps you deliver elegant, effective solutions with confidence.What You Will Learn:- Apply computational thinking to complex C++ problems- Break problems into components using abstraction- Use algorithms and data structures effectively in C++- Design modular and reusable C++ code- Analyze and improve algorithmic performance- Parse, transform, and interpret data in multiple formats- Scale up with concurrency, GPUs, and profiling toolsWho this book is for:C++ developers, software engineers, and computer science students who want to enhance their problem-solving capabilities and build scalable, maintainable solutions. Basic familiarity with C++ syntax is assumed, making this ideal for intermediate programmers ready to master abstraction and algorithmic thinking.Table of Contents- Thinking computationally- Abstraction in detail- Algorithmic thinking and complexity- Understanding the machine- Data structure- Reusing Your Code and Modularity- Outlining the Challenge- Building a simple command line interface- Reading Data from Different Formats- Finding Information in Text- Clustering Data- Reflecting on what we have built- The Problems of Scale- Dealing with GPUs and Specialized Hardware- Profiling with Code
