Models and Measurements for Quality Assessment of Software
ACM Computing Surveys (CSUR)
On a measure of program structure
Programming Symposium, Proceedings Colloque sur la Programmation
A model for program complexity analysis
ICSE '78 Proceedings of the 3rd international conference on Software engineering
IEEE Transactions on Software Engineering
HIPO and integrated program design
IBM Systems Journal
IBM Systems Journal
Information theoretical analysis of multivariate correlation
IBM Journal of Research and Development
Complexity metrics for cascading style sheets
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part IV
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Several metrics for the quality assessment of a software system design are discussed. The metrics are based on the entropy function of communication information theory. The design of software systems is viewed as a trade-off between the information contained within a subsystem and the information shared among the subsystems of a given system. Since information can be shared in different ways by different system designs, we can compute the excess entropy and thereby rank different design alternatives. Consequently, the quality improvement due to reconfigurations can be determined by calculating the excess entropies for each reconfiguration.