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Hands-On High Performance Programming with Qt 5

You're reading from   Hands-On High Performance Programming with Qt 5 Build cross-platform applications using concurrency, parallel programming, and memory management

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789531244
Length 384 pages
Edition 1st Edition
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Author (1):
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Marek Krajewski Marek Krajewski
Author Profile Icon Marek Krajewski
Marek Krajewski
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Table of Contents (14) Chapters Close

Preface 1. Understanding Performant Programs 2. Profiling to Find Bottlenecks FREE CHAPTER 3. Deep Dive into C++ and Performance 4. Using Data Structures and Algorithms Efficiently 5. An In-Depth Guide to Concurrency and Multithreading 6. Performance Failures and How to Overcome Them 7. Understanding I/O Performance and Overcoming Related Problems 8. Optimizing Graphical Performance 9. Optimizing Network Performance 10. Qt Performance on Embedded and Mobile Platforms 11. Testing and Deploying Qt Applications 12. Assessments 13. Other Books You May Enjoy

Chapter 4

  1. If a better algorithm uses knowledge about the structure of the data, how does that apply to sorting? Is the data to be sorted by definition devoid of any structure?
    There is one fundamental thing we know here—data can be partitioned and sorted into smaller chunks, thus decreasing the complexity from O(n2) to O(n log n). There aren't any neighborhood considerations to be taken into account. And, apart from that, sorting algorithms do use additional knowledge. Time sort (used in Python) is optimized for nearly-sorted array cases. The C++ STL's sort algorithm will switch from quicksort to insertion sort for small inputs or small subpartitions of the data.
  1. Is using the QStringList class a good idea? Or should you use QVector<QString> instead?
    QString is declared with Q_DECLARE_SHARED, which makes it movable. QStringList is a typedef for QList&lt...
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