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Design size metrics measure the size of design elements, typically by counting the elements contained within. For example, the number of operations in a class, the number of classes in a package, and so on.
Impact on quality
Size metrics are good candidates for developing cost or effort estimates for implementation, review, testing, or maintenance activities. Such estimates are then used as input for project planning purposes and the allocation of personnel.
In addition, large sized design elements (e.g., big classes or packages) may suffer from poor design. In an iterative development process, more and more functionality is added to a class or package over time. The danger is that, eventually, many unrelated responsibilities are assigned to a design element. As a result, it has low functional cohesion. This in turn negatively impacts the understandability, reusability, and maintainability of the design element.
Therefore, interfaces and implementations of large classes or packages should be reviewed for functional cohesion. If there is no justification for the large size, the design element should be considered for refactoring, for instance, extract parts of the functionality to separate, more cohesive classes.
Empirical results
Empirical studies consistently confirm the importance of size as the main cost driver in a software project. Size metrics are also consistently good indicators of fault-proneness: large methods/classes/packages contain more faults. However, since size metrics systematically identify large design elements as fault-prone, these metrics alone are not suitable to find elements with high fault density.
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Section 6.2 "Structural Design Properties" | Contents | Section 6.2.2 "Coupling" |