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Proceedings of the Fifth International Workshop on Testing Database Systems - DBTest '12 - Targeted genetic test SQL generation for the DB2 database by Letarte, Dominic; Gauthier, Francois; Merlo, Ettore; Sutyanyong, Nattavut; Zuzarte, Calisto is a scholarly article available to read on EtoBox.
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Automatic Query generators have been shown to be effective tools for software testing. For the most part, they have been used in system testing for the database as a whole or to generate specific queries to test specific features with not much randomness. In this work we explore the problems encountered when using a genetic algorithm to generate SQL for testing a large database system. General random SQL generation that tests the database system as a whole using genetic algorithms is relatively simple. One would need to generate millions of test cases to have a reasonable chance of hitting specific combinations of features. In order to optimize the testing, one needs to generate targeted SQL queries that narrow the testing to specific feature areas and feature combinations but yet preserve a certain amount of randomness and exploit the strength of a genetic algorithm. To do this effectively, the test generator needs to be guided so that it does not stray too much from the goals of the more targeted test requirement. In this work we explore a genetic algorithm approach to generate test queries that exercise target sub-sequences of features. Genetic algorithm parameters such as genom
- Author
- Letarte, Dominic; Gauthier, Francois; Merlo, Ettore; Sutyanyong, Nattavut; Zuzarte, Calisto
- Publisher
- ACM Press
- Published
- 2012
- Language
- EN