An Empirical Study of Software Metrics
IEEE Transactions on Software Engineering
Evaluating Software Complexity Measures
IEEE Transactions on Software Engineering
Measuring software design quality
Measuring software design quality
An experiment in software sizing with structured analysis metrics
Journal of Systems and Software
Comments on 'A Metrics Suite for Object Oriented Design'
IEEE Transactions on Software Engineering
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
Object-oriented metrics: measures of complexity
Object-oriented metrics: measures of complexity
The relationship between theory and practice in software engineering
Communications of the ACM
Empirical research in software engineering: a workshop
ACM SIGSOFT Software Engineering Notes
A relational model of data for large shared data banks
Communications of the ACM
A Framework of Software Measurement
A Framework of Software Measurement
Practical Software Maintenance: Best Practices for Managing Your Software Investment
Practical Software Maintenance: Best Practices for Managing Your Software Investment
Software Metrics: A Rigorous Approach
Software Metrics: A Rigorous Approach
Fundamentals of Database Systems
Fundamentals of Database Systems
Software Measurement: A Necessary Scientific Basis
IEEE Transactions on Software Engineering
An Experimental Comparison of the Maintainability of Object-Oriented and Structured Design Documents
ICSM '97 Proceedings of the International Conference on Software Maintenance
Metrics for Database Systems: An Empirical Study
METRICS '97 Proceedings of the 4th International Symposium on Software Metrics
Software Metrics Model For Quality Control
METRICS '97 Proceedings of the 4th International Symposium on Software Metrics
Using a qualitative research method for building a software maintenance methodology
Software—Practice & Experience
On Metamodel-Based Design of Software Metrics
Balancing Agility and Formalism in Software Engineering
Measuring and Comparing Effectiveness of Data Quality Techniques
CAiSE '09 Proceedings of the 21st International Conference on Advanced Information Systems Engineering
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Developing and selecting high quality software applications are fundamental. It is important that the software applications can be evaluated for every relevant quality characteristic using validated metrics. Software engineers have been putting forward hundreds of quality metrics for software programs, disregarding databases. However, software data aspects are important because the size of data and their system nature contribute to many aspects of a systems quality. In this paper, we proposed some internal metrics to measure relational databases which influence its complexity. Considering the main characteristics of a relational table, we can propose the number of attributes (NA) of a table, the depth of the referential tree (DRT) of a table, and the referential degree (RD) of a table. These measures are characterized using measurement theory, particularly the formal framework proposed by Zuse. As many important issues faced by the software engineering community can only be addressed by experimentation, an experiment has been carried out in order to validate these metrics.