Title:	A COMPARATIVE ANALYSIS FOR CREATING TEST-DATA IN E-HEALTH INTEGRATED INFORMATION SYSTEMS
Author(s):	Ali Raza, Stephen Clyde
ISBN:	978-972-8939-70-0
Editors:	Mário Macedo
Year:	2012
Edition:	Single
Keywords:	Testing e-Health Systems, Test-data Extraction and Generation, A Comparison study for test-beds, Federated Databases
Type:	Full Paper
First Page:	61
Last Page:	68
Language:	English
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Paper Abstract:	Testing of database-intensive e-health applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target schemes, and implicit business rules. These challenges become even more difficult when the application involves integrated databases or confidential data. Proper test-data that can simulate real-world data problems are critical to achieving reasonable quality benchmarks for functional, input-validation, load, performance, and stress testing. In general, techniques for creating test-data can be classified in two board areas; test-data generation and test-data extraction that differ significantly in their basic approach, runtime performance, and the types of data they create. This paper describes a theoretical study that establishes guidelines for software tester in making informed choices about various test-data creation techniques. We start with a more detailed categorization of different kinds of test-data creation techniques. We also illustrate the use of these techniques in existing test-data creation tools and discuss their usefulness in the context of an integrated database system with confidential data. Next, we present a method for comparing the relative strength and weakness of the different test-data creation techniques. Finally, we present the result of a comparison based on this method and analyze those result. At the highest level of analysis, we found that test-data extraction can produce more realistic test-data, whereas, test-data generators can be more efficient. However, we present a number of more specific conclusions that will help testers make appropriate choices.
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