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Hands-On High Performance Programming with Qt 5

Hands-On High Performance Programming with Qt 5

By : Marek Krajewski
5 (2)
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Hands-On High Performance Programming with Qt 5

Hands-On High Performance Programming with Qt 5

5 (2)
By: Marek Krajewski

Overview of this book

Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance. The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you’ll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains. By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature
Table of Contents (14 chapters)
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Chapter 1

  1. What is premature optimization?
    It can be defined as blindly optimizing some parts of code without having done any runtime measurements before.
  2. What did Donald Knuth really say about it?
    He said that programmers waste enormous amounts of time thinking about, or worrying about, the speed of non-critical parts of their programs, and these attempts at efficiency actually have a strong negative impact when debugging and maintenance are considered. We should forget about small efficiencies, say, about 97% of the time: premature optimization is the root of all evil. Yet we should not pass up our opportunities in that critical 3%.
  3. Why do we need performance optimization techniques?
    We want to decrease power consumption and enable a smooth user experience when interacting with the program.
  4. Which is the worst premature pessimization you can do?
    Choosing an inefficient algorithm...

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