Comment optimiser les performances à l’aide du polymorphisme et de la liaison dynamique ?

A practical example of polymorphism can be seen in RPG games. RPGs often include a variety of character abilities like healing, attacking, and buffing. By employing polymorphism, one can create a generic Ability class with common methods such as Activate() and Cooldown(). Specific abilities like healing or attacking then become subclasses that implement these methods in their own unique ways. This approach streamlines the management of each ability through a unified interface, while still allowing for distinct behaviors. Moreover, it simplifies system expansion, as introducing a new ability merely requires implementing the base Ability class methods.

Dynamic binding, also known as dynamic dispatching, is essential for implementing polymorphism and is commonly facilitated through virtual functions in languages like Java, C#, and C++. Expanding on the Abilities example, dynamic dispatching enables the code to invoke the Activate() method on a generic Ability class object, without needing to know its specific subclass type—be it healing, attacking, or buffing. This allows the program to execute the behavior specific to that ability at runtime, thereby enhancing both code flexibility and efficiency.

Polymorphism enables you to write more reusable and modular code by designing classes and methods to operate on abstract interfaces or base classes. This allows you to write generic algorithms and data structures that can be used with different concrete implementations without modification. Reusing code through polymorphism reduces duplication and promotes a more efficient use of resources, leading to performance improvements through reduced memory footprint and optimised execution paths.

Optimizes memory and execution time by avoiding unnecessary casts and checks: This part is not very clear. While dynamic binding can reduce the need for explicit casts and type checks in code (thus simplifying the code), it doesn't inherently optimize memory usage or execution time. I think dynamic binding introduces a small performance overhead as the method to be executed is determined at runtime rather than at compile time. This overhead is generally negligible for most applications but can be significant in highly performance-sensitive systems.

As I often suggest, code examples are paramount for articles like these. Without them, ideas like Polymorphism and Dynamic binding can seen too abstract. I suggest adding code samples of the classic Shape polymorphism example which the article covers, in a common, user friendly language, like javascript or python.