Understanding Quality in Conceptual Modeling
IEEE Software
Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
Integrating the understanding of quality in requirements specification and conceptual modeling
ACM SIGSOFT Software Engineering Notes
Investigating quality factors in object-oriented designs: an industrial case study
Proceedings of the 21st international conference on Software engineering
Metrics for controlling database complexity
Developing quality complex database systems
Software Measurement: A Necessary Scientific Basis
IEEE Transactions on Software Engineering
Towards a Deeper Understanding of Quality in Requirements Engineering
CAiSe '95 Proceedings of the 7th International Conference on Advanced Information Systems Engineering
YAM2 (Yet Another Multidimensional Model): An Extension of UML
IDEAS '02 Proceedings of the 2002 International Symposium on Database Engineering & Applications
Data & Knowledge Engineering - Special issue: Quality in conceptual modeling
Metrics for data warehouse conceptual models understandability
Information and Software Technology
Defining and validating metrics for assessing the understandability of entity-relationship diagrams
Data & Knowledge Engineering
A set of quality indicators and their corresponding metrics for conceptual models of data warehouses
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Complexity metric for multidimensional models for data warehouse
Proceedings of the CUBE International Information Technology Conference
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Multidimensional conceptual models have been accepted as the foundation for data warehouse designs. The quality of these models have significant effect on the quality of data warehouse and hence, in turn on the information quality. Few researchers have defined quality attributes for the conceptual models for data warehouse and have also proposed metrics to assess the quality attributes of these models objectively. The objective of this work is to propose candidate metrics to compute the structural complexity of multidimensional model. The main emphasis of this paper will be on the dimension hierarchies in multidimensional model. Though, these hierarchies play very significant role in analysing data at various granularity levels, their use enhances structural complexities of multidimensional model which can affect their understandability and modifiability and in turn maintainability.