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Incremental test data generation for database queries

Autor(es) y otros:
Suárez Cabal, María JoséAutoridad Uniovi; Riva Álvarez, Claudio A. de laAutoridad Uniovi; Tuya González, Pablo JavierAutoridad Uniovi; Blanco Aguirre, RaquelAutoridad Uniovi
Palabra(s) clave:

software testing

database testing

test database generation

test coverage

constraint satisfaction problem (CSP)

software engineering

Fecha de publicación:
2017-12
Editorial:

Springer Nature

Versión del editor:
https://www.doi.org/10.1007%2Fs10515-017-0212-7
Citación:
Automated Software Engineering, 24(4), p. 719-755 (2017); doi:10.1007%2Fs10515-017-0212-7
Descripción física:
p. 719-755
Resumen:

Testing database applications is a complex task since it involves designing test databases with meaningful test data in order to reveal faults and, at the same time, with a small size in order to carry out the testing process in an efficient way. This paper presents an automated approach to generating test data (test relational databases and test inputs for query parameters) for a set of SQL queries, with the aim of covering test requirements as obtained from said queries. The test data generation follows an incremental approach where, in each increment, test data are generated to cover a test requirement by re-using test data previously generated for other test requirements. The test data generation for each test requirement is formulated as a constraint satisfaction problem, where constraints are derived from the test requirement, initial database states and previously generated test data. The generation process is fully automated and supports the execution on complex queries and databases. Evaluation is carried out on a real life application, and the results show that small-size generated test relational databases achieve high coverage scores for the queries under test in a short generating time.

Testing database applications is a complex task since it involves designing test databases with meaningful test data in order to reveal faults and, at the same time, with a small size in order to carry out the testing process in an efficient way. This paper presents an automated approach to generating test data (test relational databases and test inputs for query parameters) for a set of SQL queries, with the aim of covering test requirements as obtained from said queries. The test data generation follows an incremental approach where, in each increment, test data are generated to cover a test requirement by re-using test data previously generated for other test requirements. The test data generation for each test requirement is formulated as a constraint satisfaction problem, where constraints are derived from the test requirement, initial database states and previously generated test data. The generation process is fully automated and supports the execution on complex queries and databases. Evaluation is carried out on a real life application, and the results show that small-size generated test relational databases achieve high coverage scores for the queries under test in a short generating time.

URI:
http://hdl.handle.net/10651/57781
ISSN:
0928-8910
DOI:
10.1007%2Fs10515-017-0212-7
Patrocinado por:

Projects TIN2013-46928-C3-1-R and TIN2016- 76956-C3-1-R, funded by the Spanish Ministry of Science and Technology, and GRUPIN14-007, funded by the Principality of Asturias (Spain) and ERDF funds.

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