Abstract
Till now, a large variety of researchers have carried out lots of efforts on object-oriented and UML model metrics from different views. They put forward numerous of metrics and carried out some series of theoretical and experimental verifications on understandability, analyzability, maintainability, fault-proneness, change-proneness and reuse. However, there is no formal semantic specification for UML model metrics, which may lead to potential semantic inconsistency and ambiguity. To solve this problem, this paper provided formalization for UML model metrics at the level of UML Meta models. This formalization can not only help people to understand the meaning of UML model metrics, but also can be used in the application domain of UML model metrics in a more rigorous way.
Highlights
A large variety of researchers have carried out lots of efforts on object-oriented and UML model metrics from different views
Researchers carried out some series of theoretical and experimental verifications[5,6], especially predicted external characteristics of software based on object-oriented and UML model metrics, such as understandability], analyzability, maintainability, fault-proneness, change-proneness and reuse
There is a small amount of formalization for object-oriented metrics [7,8,9,10], there is little formalization for UML model metrics, which may lead to different interpretations, potential semantic inconsistency and ambiguity
Summary
A large variety of researchers have carried out lots of efforts on object-oriented and UML model metrics from different views. There is a small amount of formalization for object-oriented metrics [7,8,9,10], there is little formalization for UML model metrics, which may lead to different interpretations, potential semantic inconsistency and ambiguity. To solve this problem, this paper provides a formal description for UML model metrics. This formalization can help people to understand the meaning of object-oriented metrics, and can be used in the application domain of object-oriented metrics in a more rigorous way
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