Book Image

Mastering Delphi Programming: A Complete Reference Guide

By : Primož Gabrijelčič
Book Image

Mastering Delphi Programming: A Complete Reference Guide

By: Primož Gabrijelčič

Overview of this book

Delphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for most operating systems, including Microsoft Windows, iOS, and now Linux with RAD Studio 10.2. If you know how to use the features of Delphi, you can easily create scalable applications in no time. This Learning Path begins by explaining how to find performance bottlenecks and apply the correct algorithm to fix them. You'll brush up on tricks, techniques, and best practices to solve common design and architectural challenges. Then, you'll see how to leverage external libraries to write better-performing programs. You'll also learn about the eight most important patterns that'll enable you to develop and improve the interface between items and harmonize shared memories within threads. As you progress, you'll also delve into improving the performance of your code and mastering cross-platform RTL improvements. By the end of this Learning Path, you'll be able to address common design problems and feel confident while building scalable projects. This Learning Path includes content from the following Packt products: Delphi High Performance by Primož Gabrijel?i? Hands-On Design Patterns with Delphi by Primož Gabrijel?i?
Table of Contents (19 chapters)

Fixing the Algorithm

In the previous chapter, we explored the concept of performance and looked at different scenarios where we would like to make the program faster. The previous chapter was largely theoretical, but now is the time to look at it in a more practical way.

There are two main approaches to speeding up a program:

  • Replace the algorithm with a better one.
  • Fine-tune the code so that it runs faster.

I spent lots of time in the previous chapter discussing the time complexity simply to make it clear that a difference between two algorithms can result in impressive speed-up. It can be much more than a simple constant factor (such as a 10-times speed-up). If we go from an algorithm with bad time complexity (say, O(n2)) to an algorithm with a better behavior (O(n log n), for example), then the difference in speed becomes more and more noticeable when we increase...