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Query-based test generation for database applications

Published: 13 June 2008 Publication History

Abstract

This paper describes a new approach to generating inputs to database applications. The goal is to generate inputs that satisfy certain properties specified by the tester and that also cause queries to return non-empty result sets and cause updates and inserts to execute without violating uniqueness or referential integrity constraints. Based on the SQL statements in the application, test generation queries are generated; execution of these queries yields test inputs with the desired properties. The test generation algorithm is described and illustrated by an example. The technique has been implemented and experimental evaluation is in progress.

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Cited By

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  • (2022)A Scalable Query-Aware Enormous Database Generator for Database EvaluationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3153651(1-1)Online publication date: 2022
  • (2018)Search-based test data generation for SQL queriesProceedings of the 40th International Conference on Software Engineering10.1145/3180155.3180202(1220-1230)Online publication date: 27-May-2018
  • (2017)Incremental test data generation for database queriesAutomated Software Engineering10.1007/s10515-017-0212-724:4(719-755)Online publication date: 1-Dec-2017
  • Show More Cited By

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cover image ACM Conferences
DBTest '08: Proceedings of the 1st international workshop on Testing database systems
June 2008
74 pages
ISBN:9781605582337
DOI:10.1145/1385269
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 13 June 2008

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Author Tags

  1. database
  2. software testing

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SIGMOD/PODS '08
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Overall Acceptance Rate 31 of 56 submissions, 55%

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Cited By

View all
  • (2022)A Scalable Query-Aware Enormous Database Generator for Database EvaluationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3153651(1-1)Online publication date: 2022
  • (2018)Search-based test data generation for SQL queriesProceedings of the 40th International Conference on Software Engineering10.1145/3180155.3180202(1220-1230)Online publication date: 27-May-2018
  • (2017)Incremental test data generation for database queriesAutomated Software Engineering10.1007/s10515-017-0212-724:4(719-755)Online publication date: 1-Dec-2017
  • (2016)Coverage-Aware Test Database ReductionIEEE Transactions on Software Engineering10.1109/TSE.2016.251903242:10(941-959)Online publication date: 1-Oct-2016
  • (2016)Pairwise Coverage-Based Testing with Selected Elements in a Query for Database Applications2016 IEEE Ninth International Conference on Software Testing, Verification and Validation Workshops (ICSTW)10.1109/ICSTW.2016.19(92-101)Online publication date: Apr-2016
  • (2015)Preventing data errors with continuous testingProceedings of the 2015 International Symposium on Software Testing and Analysis10.1145/2771783.2771792(373-384)Online publication date: 13-Jul-2015
  • (2015)Program-input generation for testing database applications using existing database statesAutomated Software Engineering10.1007/s10515-014-0158-y22:4(439-473)Online publication date: 1-Dec-2015
  • (2015)ReX: Extrapolating Relational Data in a Representative WayData Science10.1007/978-3-319-20424-6_10(95-107)Online publication date: 11-Jun-2015
  • (2014)Guided test generation for database applications via synthesized database interactionsACM Transactions on Software Engineering and Methodology10.1145/249152923:2(1-27)Online publication date: 4-Apr-2014
  • (2014)Identifying Data Inconsistencies Using After-State Database Testing (ASDT) FrameworkProceedings of the 2014 14th International Conference on Quality Software10.1109/QSIC.2014.39(105-110)Online publication date: 2-Oct-2014
  • Show More Cited By

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