Abstract
The number of concepts in a model has been frequently used in the literature to measure the ease of use in creating model schemas. However, to the best of our knowledge, nobody has looked at its effect on the readability of the model schemas after they have been created. The readability of a model schema is important in situations where the schemas are created by one team of analysts and read by other analysts, system developers, or maintenance administrators. Given the recent trend of models with increasing numbers of concepts such as the unified modeling language (UML), the effect of the number of concepts (NOC) on the readability of schemas has become increasingly important. In this work, we operationalize readability along three dimensions: effectiveness, efficiency, and learnability. We draw on the Bunge Wand Weber (BWW) framework, as well as the signal detection recognition theory and the ACT theory from cognitive psychology to formulate hypotheses and conduct an experiment to study the effects of the NOC in a data model on these readability dimensions. Our work makes the following contributions: (a) it extends the operationalization of the readability construct, and (b) unlike earlier empirical work that has focused exclusively on comparing models that differ along several dimensions, this work proposes an empirical methodology that isolates the effect of a model-independent variable (the NOC) on readability. From a practical perspective, our findings have implications both for creators of new models, as well as for practitioners who use currently available models for creating schemas to communicate requirements during the entire lifecycle of a system.
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Notes
In this work, the terms “conceptual model” or “model” refer to the modeling method. We refer to the application of a modeling method for a particular situation as a “model schema”.
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Appendix
Appendix
Figure 2 shows the library schema for the base line NOC model. Figure 3 shows the library schema for the higher level NOC model. The questionnaire following Figure 2 was used to measure the mapping from the schema to the underlying domain.
1.1 Questionnaire to test mapping to the underlying domain
For each question, please select the right choice (only one choice per question). Our answers should not be based on actual library systems, but on what is represented in the model schema:
1. Every book needs to have at least one subject area
_____True
_____False
_____Can’t tell from the model schema
2. Users can reserve and checkout the same book at the same time
_____True
_____False
_____Can’t tell from the model schema
3. An author can write books in multiple subject areas
_____True
_____False
_____Can’t tell from the model schema
4. A book can be on multiple shelves at the same time
_____True
_____False
_____Can’t tell from the model schema
5. A reading area can be near multiple shelves
_____True
_____False
_____Can’t tell from the model schema
6. From the schema, we can determine which user is sitting on which chair in the library
_____True
_____False
_____Can’t tell from the model schema
7. We can find out the number of books checked out by the user in a year
_____True
_____False
_____Can’t tell from the model schema
8. A book can have multiple checkouts on the same date
_____True
_____False
_____Can’t tell from the model schema
9. We can tell which users are interested in which subject areas
_____True
_____False
_____Can’t tell from the model schema
10. We can tell which author has the most checkouts
_____True
_____False
_____Can’t tell from the model schema
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Bajaj, A. The effect of the number of concepts on the readability of schemas: an empirical study with data models. Requirements Eng 9, 261–270 (2004). https://doi.org/10.1007/s00766-004-0202-8
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DOI: https://doi.org/10.1007/s00766-004-0202-8