Abstract conceptual database model approach
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2013
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Abstract
One of the main objectives of the software engineers is to provide software related solutions for social problems and to increase the availability of social welfare. In that sense, the quality of the software is directly related to address the users' needs and their level of satisfaction. To reflect user requirements to the software processes, the correct design of the database model provides a critical stage during software development. Database design is a fundamental tool for modeling all the requirements related to users' data. The possible faulty conditions in database design have adverse effects on all of the software development processes. The possible faulty conditions can also cause continuous changes in the software and the desired functionality of the targeted system which may result in user dissatisfaction. In this context, reflecting the user requirements accurately in the database model and understanding of the database model correctly by every person involved in the software development process is the factor that directly affects the success of software systems' development. In this study, a two-stage conceptual data modeling approach is proposed to reduce the level of complexity, to improve the understandability of database models and to improve the quality of the software. This study first describes the proposed two-stage conceptual data modeling. Than the proposed method's impact on software engineers' comprehension is also investigated and the results are compared with the degree of complexity of the related conceptual data models. Results of this study show that, the proposed two-stage conceptual modeling approach improves the understanding levels of software engineers and eliminated possible defects in this stage. © 2013 The Science and Information Organization.
Description
The Science and Information (SAI) Organization; Springer
Keywords
conceptual data model, database, entropy, software development process, structural complexity
Turkish CoHE Thesis Center URL
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4
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Source
Proceedings of 2013 Science and Information Conference, SAI 2013 -- 2013 Science and Information Conference, SAI 2013 -- 7 October 2013 through 9 October 2013 -- London -- 101986
Volume
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Start Page
275
End Page
281