Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31903
Testing Database of Information System using Conceptual Modeling

Authors: Bogdan Walek, Cyril Klimes


This paper focuses on testing database of existing information system. At the beginning we describe the basic problems of implemented databases, such as data redundancy, poor design of database logical structure or inappropriate data types in columns of database tables. These problems are often the result of incorrect understanding of the primary requirements for a database of an information system. Then we propose an algorithm to compare the conceptual model created from vague requirements for a database with a conceptual model reconstructed from implemented database. An algorithm also suggests steps leading to optimization of implemented database. The proposed algorithm is verified by an implemented prototype. The paper also describes a fuzzy system which works with the vague requirements for a database of an information system, procedure for creating conceptual from vague requirements and an algorithm for reconstructing a conceptual model from implemented database.

Keywords: testing, database, relational database, information system, conceptual model, fuzzy, uncertain information, database testing, reconstruction, requirements, optimization

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1290


[1] Rational Unified Process, http://www-, 2012.
[2] B. Walek, "Testov├ín├¡ datab├íze informa─ìn├¡ho systému", Studentsk├í v─ødeck├í konference 2011, Ostrava 2011, pp. 218-221.
[3] B. Walek, "Testing logical structure of the information system database", International Conference on Business Intelligence and Financial Engineering, Hong Kong 2011, to be published.
[4] L. Jan Harrington, Relational database design and implementation. Elsevier Inc., Burlington, 2009, ch. 4,5.
[5] S. Lauesen, Software Requirements: Styles and Techniques, Addison- Wesley Professional, Glasgow, 2002, ch. 1,2,3.
[6] J. Bartoš, B. Walek, P. Smolka, J. Procházka, C. Klimeš, "Fuzzy modeling tools for information system testing", 17th International Conference on Soft Computing Mendel 2011, Brno 2011, pp. 154-161.
[7] V. ┼ÿepa, Anal├¢za a n├ívrh informa─ìn├¡ch systém┼», EKOPRESS, Praha 1999, pp. 146-159.
[8] C. Klimeš, "Model of adaptation under indeterminacy". In Kybernetika, Vol.47 (2011) No.3, Prague 2011, pp. 355-368.
[9] B. Walek, C. Klimeš, Fuzzy tool for conceptual modeling under uncertainty, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, Proceedings of SPIE Vol. 8349, Bellingham 2012.
[10] H. Habiballa, V. Nov├ík, A. Dvoř├ík, V. Pavliska, "Using software package LFLC 2000", 2nd International Conference Aplimat 2003, Bratislava, 2003, pp. 355-358.
[11] J. Proch├ízka, C. Klime┼í, Provozujte IT jinak: Agiln├¡ a ┼ít├¡hl├¢ provoz, podpora a ├║držba informa─ìn├¡ch systém┼» a IT služeb, Prague: Grada, 2011, ch. 8.
[12] A. Olivé, Conceptual modeling on information systems, Springer- Verlag Berlin Heidelberg, New York 2007, ch. 1.
[13] P. Atzeni, V. De Antonellis, Relational Database Theory, The Benjamin/Cummings Publishing Company, Inc., Redwood City, 1993, ch. 1.