By Topic

Performance effects of formal modeling language differences: a combined abstraction level and construct complexity analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hock-Hai Teo ; Dept. of Inf. Syst. & Comput, Nat. Univ. of Singapore, Singapore ; Hock Chuan Chan ; Kwok Kee Wei

Understanding data-modeling performance can provide valuable lessons for the selection, training, research, and development of data models. Data modeling is the process of transforming expressions in loose natural language communications into formal diagrammatic or tabular expressions. While researchers generally agree that abstraction levels can be used to explain general performance differences across models, empirical studies have reported many construct level results that cannot be explained. To explore further explanations, we develop a set of model-specific construct complexity values based on both theoretical and empirical support from complexity research in databases and other areas. We find that abstraction levels and complexity values together are capable of providing a consistent explanation of laboratory experiment data. In our experiment, data were drawn from three models: the relational model, the extended-entity-relationship model, and the object-oriented model. With the newly developed complexity measures, a consistent explanation can be made for findings from other studies which provide sufficient model details for complexity values to be calculated.

Published in:

IEEE Transactions on Professional Communication  (Volume:49 ,  Issue: 2 )