Book Image

Game Development Patterns with Unreal Engine 5

By : Stuart Butler, Tom Oliver
3.5 (2)
Book Image

Game Development Patterns with Unreal Engine 5

3.5 (2)
By: Stuart Butler, Tom Oliver

Overview of this book

Design patterns serve as a toolkit of techniques and practices that enable you to write code that’s not only faster, but also more manageable. With this book, you’ll explore a range of design patterns and learn how to apply them to projects developed in Unreal Engine 5. You’ll begin by delving into the foundational principles of coding and develop a solid understanding of the concepts, challenges, and benefits of using patterns in your code. As you progress, you’ll identify patterns that are woven into the core of Unreal Engine 5 such as Double Buffer, Flyweight, and Spatial Partitioning, followed by some of the existing tool sets that embody patterns in their design and usage including Component, Behavior Tree, and Update. In the next section of the book, you’ll start developing a series of gameplay use cases in C++ to implement a variety of design patterns such as Interface and Event-based Observers to build a decoupled communications hierarchy. You’ll also work with Singleton, Command, and State, along with Behavioral Patterns, Template, Subclass Sandbox, and Type Object. The final section focuses on using design patterns for optimization, covering Dirty Flag, Data Locality, and Object Pooling. By the end of this book, you’ll be proficient in designing systems with the perfect C++/Blueprint blend for maintainable and scalable systems.
Table of Contents (16 chapters)
1
Part 1:Learning from Unreal Engine 5
6
Part 2: Anonymous Modular Design
10
Part 3: Building on Top of Unreal

Spatial partitioning

Imagine the Matrix is a real concept, and we are living in a giant physics simulation. Anybody who has dabbled in physics simulations knows that you don’t need many interacting objects to make the simulation chug. The naïve solution is to check every object against every other object leading to an O(n2-n) solution, where you can see in Figure 3.6 that 4 objects have 12 collision checks:

Figure 3.6 – Diagram showing each collision check performed in an inefficient collision detection solution

Figure 3.6 – Diagram showing each collision check performed in an inefficient collision detection solution

Improvements can obviously be made to not repeat calculations that have already been made, bringing us down to O(nLog2(n)) where those same four points use only six collision checks. This is better, but there is only so far we can go by checking every object against every other object. We could just not calculate some of them, but that would be like giving some people in our Matrix simulation wall hacks, allowing them to possibly...