Write Powerful, Modern C++ Code for Scientific, Engineering, and Embedded Applications

Discovering Modern C++, Second Edition, will help you master valuable skills for programming with C++ at nearly every level, from "close to the hardware" to high-level abstractions.

Updated for C++17 and C++ 20, this intensive introduction teaches C++ using realistic examples from diverse technical problem domains. Drawing on extensive experience teaching C++ to physicists, mathematicians, engineers, and students, Peter Gottschling guides you smoothly to sophisticated approaches based on advanced features.

Whatever your programming experience, you'll rapidly master increasingly powerful features, from lambdas to expression and variadic templates. Gottschling also shows you how to apply C++'s libraries: both the Standard Template Library (STL) and scientific libraries for arithmetic, linear algebra, differential equations, and graphs. Step by step, you'll learn to write clear and expressive code using object orientation, generics, metaprogramming, and procedural techniques, and master all the abstractions you need to write high-quality, well-performing software.

Quickly master core features: variables, operators, expressions, statements, functions, error handling, I/O, arrays, pointers, references, and more
Make the most of classes and object-oriented programming, from constructors/destructors to operator overloading and multiple inheritance
Apply advanced generic programming and template-based techniques
Use C++'s libraries to write more robust and powerful code more quickly
Explore metaprogramming in depth, and master cutting-edge optimization techniques
Walk through representative scientific projects, and create your own

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About the Author

Peter Gottschling is founder of SimuNova, a company that develops the Matrix Template Library (MTL4) and offers C++ training. He is a member of the ISO C++ standards committee, vice-chair of Germany's programming language standards committee, and founder of the C++ User Group in Dresden. He earned his Ph.D. in computer science at Technische Universit�t Dresden in 2002.

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