Statecharts: A visual formalism for complex systems
Science of Computer Programming
Evolving good hierarchical decompositions of complex systems
Journal of Systems Architecture: the EUROMICRO Journal - Special issue on evolutionary computing
Dynamic Metrics for Object Oriented Designs
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
On the Automatic Modularization of Software Systems Using the Bunch Tool
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
The impact of structural complexity on the understandability of UML statechart diagrams
Information Sciences: an International Journal
Measures for assessing dynamic complexity aspects of object-oriented conceptual schemes
ER'00 Proceedings of the 19th international conference on Conceptual modeling
Superstate identification for state machines using search-based clustering
Proceedings of the 12th annual conference on Genetic and evolutionary computation
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Automatically generated state machines are constrained by their complexity, which can be reduced via hierarchy generation. A technique has been demonstrated for hierarchy generation, although evaluation of this technique has proved difficult. There are a variety of metrics that can be used to provide indicators of how complicated a state machine or statechart is, one such example is cyclomatic complexity (the number of edges - the number of states + 2). Despite this, the existing complexity metric for statecharts does not operate on the hierarchy, instead providing an equivalent cyclomatic complexity for statecharts by ignoring it. This paper defines two new metrics; Top Level Cyclomatic Complexity and Hierarchical Cyclomatic Complexity. These metrics assess the complexity of a hierarchical machine directly, as well as allowing for comparison between the original, flat state machine and its hierarchical counterpart.