Testing Database of Information System using Conceptual Modeling
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.
[1] Rational Unified Process, http://www-
01.ibm.com/software/awdtools/rup/, 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. Procházka, C. Klimeš, Provozujte IT jinak: Agilní a štíhlÛ 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.
[1] Rational Unified Process, http://www-
01.ibm.com/software/awdtools/rup/, 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. Procházka, C. Klimeš, Provozujte IT jinak: Agilní a štíhlÛ 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.
@article{"International Journal of Information, Control and Computer Sciences:56317", author = "Bogdan Walek and Cyril Klimes", title = "Testing Database of Information System using Conceptual Modeling", abstract = "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", volume = "6", number = "4", pages = "471-7", }