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The C++ Programmer's Mindset

The C++ Programmer's Mindset

By : Sam Morley
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The C++ Programmer's Mindset

The C++ Programmer's Mindset

By: Sam Morley

Overview of this book

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.
Table of Contents (19 chapters)
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18
Index

Computing complexity

Computational or algorithmic complexity is a measure of how the running time of an algorithm grows depending on the size of the inputs. This is a theoretical computation that is independent of the specific hardware or implementation. Computational complexity is the primary means of comparing the efficiency of different algorithms (for achieving the same aim). The analysis of algorithmic complexity can be rather tricky, so we won’t go into too much detail here.

Complexity is usually recorded in “big-oh” notation, such as , , , and . The number that appears here is the term that dominates the theoretical execution time for large enough . Here, represents constant complexity, where the operation takes a constant amount of time regardless of the size of the input; means the running time is related to the size of the inputs in a linear manner. Quadratic complexity means that the theoretical running time is dominated by the square of the...

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