C++ Programming: A Quantitative Approach

This book adopts a quantitative approach to helping programmers and CS students learn C++ fast. For every C++ programming language feature covered, the book explains the concepts clearly, followed with carefully selected, working examples. The book can also be used as a supplementary text to the traditional data structures and algorithm analysis class for CS students. Besides, if you are a job seeker and interested in learning or brushing up your C++ programming skills and then passing very strict coding tests typically required in those prominent companies such as Amazon, Apple, Facebook, and Google, this text would also be helpful, as it is not too verbose for you to grasp within a very limited timeframe (the last chapter contains some real interview coding examples that the author experienced the first hand). The book also includes an Appendix titled Back from C++ to C, which can help you quickly turn your C++ skills to C skills for passing C coding tests. The subjects covered in this book are logically organized as follows:Chapter 1 Introduction to C++Chapter 2 Some Basic C++ ConstructsChapter 3 C++ Primitive Data TypesChapter 4 C++ Control StatementsChapter 5 C++ Arrays and StringsChapter 6 C++ PointersChapter 7 C++ FunctionsChapter 8 More C++ Qualifiers and Dynamic Memory AllocationChapter 9 C++ Enumerations, Structs and UnionsChapter 10 C++ ClassesChapter 11 C++ InheritanceChapter 12 C++ PolymorphismChapter 13 C++ Operator OverloadingChapter 14 C++ TemplatesChapter 15 C++ I/O SystemChapter 16 C++ Exception HandlingChapter 17 C++ Standard Template LibraryChapter 18 Practicing C++ Programming In essence, this text helps you acquire a verifiable set of useful C++ programming skills effectively and efficiently within a timeframe of a few months.

HENRY H. LIU, PHD, is a Software Engineer specializing in developing distributed, high performing, scalable enterprise software products. He is a certified Sun Enterprise Java Architect, IBM XML Developer, and Microsoft .Net Developer. Prior to becoming a software engineer, he had a physicist career and published over 30 research papers in physics while working in the national labs of China, France, Germany, and the United States. His honors include being the author of the highly acclaimed Software Performance and Scalability: A Quantitative Approach (Wiley, 2009),  an Alexander von Humboldt Research Fellow in Germany, and a  CMG 2004 Best Paper Award recipient for applying queuing theory to analyzing software performance. He is particularly encouraged that over 600 universities/colleges world-wide have used his works in teaching software technologies to CS students.