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Complex inheritance, or inheritance used within an insufficiently mature design, may lead to the yo-yo problem. When inheritance was used as a primary approach to structure programs in the late 1990s, developers tended to break code into more layers of inheritance as the system functionality grew.
Composition over inheritance (or composite reuse principle) in object-oriented programming (OOP) is the principle that classes should favor polymorphic behavior and code reuse by their composition (by containing instances of other classes that implement the desired functionality) over inheritance from a base or parent class. [2]
Multiple inheritance is a feature of some object-oriented computer programming languages in which an object or class can inherit features from more than one parent object or parent class. It is distinct from single inheritance, where an object or class may only inherit from one particular object or class.
Using inheritance is recommended mainly when adding to the functionality of existing components, reusing most of the old code and adding relatively small amounts of new code. To the authors, 'delegation' is an extreme form of object composition that can always be used to replace inheritance.
Object-oriented programming (OOP) is a programming paradigm based on the concept of objects, [1] which can contain data and code: data in the form of fields (often known as attributes or properties), and code in the form of procedures (often known as methods).
In software development, the yo-yo problem is an anti-pattern that occurs when a programmer has to read and understand a program whose inheritance graph is so long and complicated that the programmer has to keep flipping between many different class definitions in order to follow the control flow of the program.
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They introduce six OO complexity metrics: (1) weighted methods per class; (2) coupling between object classes; (3) response for a class; (4) number of children; (5) depth of inheritance tree; and (6) lack of cohesion of methods. Several other metrics can be used to measure programming complexity: Branching complexity (Sneed Metric)