In recent years much work has been performed in developing suites of metrics that are targeted for object-oriented software, rather than functionally-oriented software. This is necessary since good object-oriented software has several characteristics, such as inheritance and polymorphism, that are not usually present in functionally-oriented software. However, all of these object-oriented metrics suites have been defined using only syntactic aspects of object-oriented software; indeed, the earlier functionally-oriented metrics were also calculated using only syntactic information. All syntactically-oriented metrics have the problem that the mapping from the metric to the quality the metric purports to measure, such as the software quality factor "cohesion," is indirect, and often arguable. Thus, a substantial amount of research effort goes into proving that these syntactically-oriented metrics actually do measure their associated quality factors.
This paper introduces a new suite of semantically-derived object-oriented metrics, which provide a more direct mapping from the metric to its associated quality factor than is possible using syntactic metrics. These semantically-derived metrics are calculated using knowledge-based, program understanding, and natural language processing techniques.'