9It is a better practice (in terms of performance) to create deep inheritance and access methods in the ancestor classes.Review LaterTrueFalse

Analysis of Deep Inheritance in Performance

1. Understanding Inheritance: In object-oriented programming, inheritance allows a class (child) to inherit properties and methods from another class (parent). Deep inheritance occurs when a class is derived from a subclass that itself is derived from another class, creating multiple layers.

2. Performance Considerations:

   • Method Resolution Order (MRO): In languages like Python, the more layers an inheritance tree has, the more complex the MRO becomes. This can lead to performance hits when methods are called, as the runtime has to search through multiple classes to resolve the method.
   • Coupling and Cohesion: Deep inheritance can lead to larger class hierarchies that can become tightly coupled, making the codebase harder to understand and maintain. This indirectly affects performance as debugging and updates may become cumbersome.

3. Trade-offs: While deep inheritance can sometimes lead to code reuse and a cleaner design, it can also introduce overhead in terms of performance and complexity. It’s often a better practice to favor composition over inheritance where appropriate.

Conclusion

Given the potential downsides associated with deep inheritance, including increased complexity and decreased performance in some cases, the statement that it is a better practice to create deep inheritance and access methods in ancestor classes is generally False.