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Inheritance-related metrics are concerned with aspects such as
Deep inheritance structures are hypothesized to be more fault-prone. The information needed to fully understand a class situated deep in the inheritance tree is spread over several ancestor classes, thus more difficult to overview.
Similar to high export coupling, a modification to a design element with a large number of descendents can have a large effect on the system. Make sure the interface of the class is stable, or that anticipated modifications can be added without affecting the inheritance hierarchy at large.
Empirical studies show that effects of the use of inheritance on system qualities such as fault-proneness vary greatly. Depending on factors such as developer experience, system quality can benefit or suffer from the use of inheritance, or be unaffected by it.
Thus, inheritance metrics should not be relied on for decision making before their impact on system quality is not demonstrated in a given development environment. Extant inheritance metrics per se are not suitable to distinguish proper use of inheritance from improper use.
Also, inheritance is not very frequently used in designs. Typically, only a small percentage of the classes in a system will participate in inheritance relationships. As a consequence, inheritance-related metrics tend to have low variance and are difficult to use (see Section 6.3.1 "Descriptive Statistics").
|Section 6.2.2 "Coupling"||Contents||Section 6.2.4 "Complexity"|