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International Conference on Conceptual Modeling

ER 2013: Conceptual Modeling pp 227–240Cite as

Effective Recognition and Visualization of Semantic Requirements by Perfect SQL Samples

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8217))

Abstract

SQL designs result from methodologies such as UML or Entity-Relationship models, description logics, or relational normalization. Independently of the methodology, sample data is promoted by academia and industry to visualize and consolidate the designs produced. SQL table definitions are a standard-compliant encoding of their designers’ perception about the semantics of an application domain. Armstrong sample data visualize these perceptions. We present a tool that computes Armstrong samples for different classes of SQL constraints. Exploiting our tool, we then investigate empirically how these Armstrong samples help design teams recognize domain semantics. New measures empower us to compute the distance between constraint sets in order to evaluate the usefulness of our tool. Extensive experiments confirm that users of our tool are likely to recognize domain semantics they would overlook otherwise. The tool thereby effectively complements existing design methodologies in finding quality schemata that process data efficiently.

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Author information

Authors and Affiliations

  1. School of Information Management, Victoria University of Wellington, New Zealand

    Van Bao Tran Le & Flavio Ferrarotti

  2. Department of Computer Science, University of Auckland, Auckland, New Zealand

    Sebastian Link

Authors
  1. Van Bao Tran Le
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  2. Flavio Ferrarotti
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China

    Wilfred Ng

  2. Department of Computer Information Systems, J. Mack Robinson College of Business, Georgia State University, USA

    Veda C. Storey

  3. University of Allicante, 03690, Allicante, Spain

    Juan C. Trujillo

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Le, V.B.T., Link, S., Ferrarotti, F. (2013). Effective Recognition and Visualization of Semantic Requirements by Perfect SQL Samples. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds) Conceptual Modeling. ER 2013. Lecture Notes in Computer Science, vol 8217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41924-9_20

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  • DOI: https://doi.org/10.1007/978-3-642-41924-9_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41923-2

  • Online ISBN: 978-3-642-41924-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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