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Creating Datasets for Testing Relational Databases: Test-data Exaction and Comparison with Test-data Generation - Softcover
Inhaltsangabe
Testing of database-intensive applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target database schemes, and implicit business rules. These challenges become even more difficult when the application involves integrated and heterogeneous databases or confidential data. Proper test-data that 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 fall in two broad areas, namely, test-data generation and test-data extraction, that differ significantly in their basic approach, run-time performance, and the types of data they create. Test-data generation relies on generation rules, grammars, and pre-defined domains to create data from scratch. Test-data extraction takes sample data from existing production databases and manipulates that data for testing purposes, while trying to maintain the natural characteristics of the data. This title provides novel test-data extraction techniques and compares it with competing test-data generation.
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Testing of database-intensive applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target database schemes, and implicit business rules. These challenges become even more difficult when the application involves integrated and heterogeneous databases or confidential data. Proper test-data that 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 fall in two broad areas, namely, test-data generation and test-data extraction, that differ significantly in their basic approach, run-time performance, and the types of data they create. Test-data generation relies on generation rules, grammars, and pre-defined domains to create data from scratch. Test-data extraction takes sample data from existing production databases and manipulates that data for testing purposes, while trying to maintain the natural characteristics of the data. This title provides novel test-data extraction techniques and compares it with competing test-data generation.
Biografía del autor
Raza received an MS (Computer Science) from Utah State University and has several years of software development experience. His primary interests are Object-oriented Software Engineering, Software Testing and Relational Databases. When not writing or reading about his interest, he likes to play table tennis and traveling.
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Creating Datasets for Testing Relational Databases
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3847337637
ISBN 13: 9783847337638
Neu
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Raza AliRaza received an MS (Computer Science) from Utah State University and has several years of software development experience. His primary interests are Object-oriented Software Engineering, Software Testing and Relational Datab. Bestandsnummer des Verkäufers 5511009
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Creating Datasets for Testing Relational Databases
Verlag:
LAP LAMBERT Academic Publishing Jan 2012, 2012
ISBN 10: 3847337637
ISBN 13: 9783847337638
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -Testing of database-intensive applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target database schemes, and implicit business rules. These challenges become even more difficult when the application involves integrated and heterogeneous databases or confidential data. Proper test-data that 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 fall in two broad areas, namely, test-data generation and test-data extraction, that differ significantly in their basic approach, run-time performance, and the types of data they create. Test-data generation relies on generation rules, grammars, and pre-defined domains to create data from scratch. Test-data extraction takes sample data from existing production databases and manipulates that data for testing purposes, while trying to maintain the natural characteristics of the data. This title provides novel test-data extraction techniques and compares it with competing test-data generation.Books on Demand GmbH, Überseering 33, 22297 Hamburg 188 pp. Englisch. Bestandsnummer des Verkäufers 9783847337638
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Creating Datasets for Testing Relational Databases
Verlag:
LAP LAMBERT Academic Publishing Jan 2012, 2012
ISBN 10: 3847337637
ISBN 13: 9783847337638
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Testing of database-intensive applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target database schemes, and implicit business rules. These challenges become even more difficult when the application involves integrated and heterogeneous databases or confidential data. Proper test-data that 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 fall in two broad areas, namely, test-data generation and test-data extraction, that differ significantly in their basic approach, run-time performance, and the types of data they create. Test-data generation relies on generation rules, grammars, and pre-defined domains to create data from scratch. Test-data extraction takes sample data from existing production databases and manipulates that data for testing purposes, while trying to maintain the natural characteristics of the data. This title provides novel test-data extraction techniques and compares it with competing test-data generation. 188 pp. Englisch. Bestandsnummer des Verkäufers 9783847337638
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Creating Datasets for Testing Relational Databases : Test-data Exaction and Comparison with Test-data Generation
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3847337637
ISBN 13: 9783847337638
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Testing of database-intensive applications has unique challenges that stem from hidden dependencies, subtle differences in data semantics, target database schemes, and implicit business rules. These challenges become even more difficult when the application involves integrated and heterogeneous databases or confidential data. Proper test-data that 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 fall in two broad areas, namely, test-data generation and test-data extraction, that differ significantly in their basic approach, run-time performance, and the types of data they create. Test-data generation relies on generation rules, grammars, and pre-defined domains to create data from scratch. Test-data extraction takes sample data from existing production databases and manipulates that data for testing purposes, while trying to maintain the natural characteristics of the data. This title provides novel test-data extraction techniques and compares it with competing test-data generation. Bestandsnummer des Verkäufers 9783847337638
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Creating Datasets for Testing Relational Databases: Test-data Exaction and Comparison with Test-data Generation
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3847337637
ISBN 13: 9783847337638
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Paperback. Zustand: Like New. Like New. book. Bestandsnummer des Verkäufers ERICA79638473376376
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