Book Image

Delphi High Performance - Second Edition

By : Primož Gabrijelčič
5 (1)
Book Image

Delphi High Performance - Second Edition

5 (1)
By: Primož Gabrijelčič

Overview of this book

Performance matters! Users hate to use programs that are not responsive to interactions or run too slow to be useful. While becoming a programmer is simple enough, you require dedication and hard work to achieve an advanced level of programming proficiency where you know how to write fast code. This book begins by helping you explore algorithms and algorithmic complexity and continues by describing tools that can help you find slow parts of your code. Subsequent chapters will provide you with practical ideas about optimizing code by doing less work or doing it in a smarter way. The book also teaches you how to use optimized data structures from the Spring4D library, along with exploring data structures that are not part of the standard Delphi runtime library. The second part of the book talks about parallel programming. You’ll learn about the problems that only occur in multithreaded code and explore various approaches to fixing them effectively. The concluding chapters provide instructions on writing parallel code in different ways – by using basic threading support or focusing on advanced concepts such as tasks and parallel patterns. By the end of this book, you’ll have learned to look at your programs from a totally different perspective and will be equipped to effortlessly make your code faster than it is now.
Table of Contents (15 chapters)

Algorithm complexity

Before we start with the dirty (and fun) job of improving program speed, I’d like to present a bit of computer science theory, namely, Big O notation.

You don’t have to worry, I will not use pages of mathematical formulas and talk about infinitesimal asymptotes. Instead, I will just present the essence of Big O notation, the parts that are important to every programmer.

In the literature and, of course, on the web, you will see expressions such as O(n), O(n^2), O(1), and similar. This fancy-looking notation hides a really simple story. It tells us how much slower the algorithm will become if we increase the data size by a factor of n.

Information

The n^2 notation means “n to the power of two,” or n2. This notation is frequently used on the internet because it can be written with standard ASCII characters. This book uses the more readable variant, O(n2).

Let’s say we have an algorithm with a complexity of O(n), which...