Abstract
It is possible to use different designs to deal with the missing information problem in SQL databases. In this paper, we use a multi-criteria decision support method, which is based on the Analytic Hierarchy Process, to evaluate a set of possible designs for dealing with missing information. One of the designs uses SQL NULL-marks, another design uses tables that are in the sixth normal form, and one of the designs uses special values to represent missing information. We evaluate the designs, which are implemented in a PostgreSQLâ„¢ database, in terms of two hypothetical contexts. We create a test database, perform measurements, and use the results to compare the designs. The results of the evaluation provide new insights into the advantages and disadvantages of the different designs.
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References
Melton J (2006) IWD 9075-1:200x(E) information technology—database languages—SQL—Part 1: framework (SQL/framework). Feb 2006
Date CJ (2003) An introduction to database systems, 8th edn. Pearson/Addison Wesley, Boston
Date CJ, Darwen H (2007) Databases, types, and the relational model. The Third Manifesto, 3rd edn. Addison-Wesley
Date CJ (2009) SQL and relational theory. How to write accurate SQL code. O’Reilly, Romulus, MI
Date CJ, Darwen H (2010) Database explorations. Essays on the third manifesto and related topics. Trafford Publishing, San Francisco
Rönnbäck L, Regardt O, Bergholtz M, Johannesson P, Wohed P (2010) Anchor Modeling. Agile information modeling in evolving data environments. Data Knowl Eng 69(12), 1229–1253
Karwin B (2010) SQL antipatterns. Avoiding the pitfalls of database programming. The pragmatic bookshelf
PredictiveDB, [Online document]. Accessed 5 aug 2011 http://www.predictivedb.com/.
Codd EF (1990) The relational model for database management: version 2. Addison-Wesley, Menlo Park
Liu K-C, Sunderraman R (1990) Indefinite and maybe information in relational databases, ACM Trans Database Syst 15(1), 1–39
Date CJ, Darwen H (2000) Foundation for future database systems. The third manifesto, 2nd edn. Addison-Wesley, Massachusetts
Eessaar E, Soobik M (2012) A decision support method for evaluating database designs. Comput Sci Inf Syst 4:345–365
Saaty TL (1994) How to make a decision: the analytic hierarchy process. Interfaces 24(6):19–43
ISO/IEC 9126-1, Software engineering–product quality–Part 1: quality model, first edn.: 2001-06-15
PostgreSQL 8.3 Documentation, [Online document]. Accessed 9 Aug 2009 http://www.postgresql.org/docs/.
Gornik D, UML data modeling profile. In: Rational software white paper TP162, 05/2002
Date CJ (2006) The relational database dictionary. A comprehensive glossary of relational terms and concepts, with illustrative examples. O’Reilly, Punta Gorda, FL
Piattini M, Calero C, Sahraoui H, Lounis H (2001) Object-relational database metrics. L’Object 2:488–494
Baroni AL, Calero C, Abreu FB, Piattini M (2006) Object-relational database metrics formalization. In: Sixth international conference on quality software, pp 30–37
Mustajoki J, Hamalainen RP (2000) Web-HIPRE: global decision support by value tree and AHP analysis. INFOR 38(3):208–220
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Eessaar, E., Saal, E. (2013). Evaluation of Different Designs to Represent Missing Information in SQL Databases. In: Elleithy, K., Sobh, T. (eds) Innovations and Advances in Computer, Information, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3535-8_14
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DOI: https://doi.org/10.1007/978-1-4614-3535-8_14
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