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Coverage-aware test database reduction

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

Test database reduction

Test coverage of code

Test design

Testing tools

Fecha de publicación:
2016
Editorial:

IEEE

Versión del editor:
http://dx.doi.org/10.1109/TSE.2016.2519032
Citación:
IEEE Transactions on Software Engineering (2016); doi:10.1109/TSE.2016.2519032
Resumen:

Functional testing of applications that process the information stored in databases often requires a careful design of the test database. The larger the test database, the more difficult it is to develop and maintain tests as well as to load and reset the test data. This paper presents an approach to reduce a database with respect to a set of SQL queries and a coverage criterion. The reduction procedures search the rows in the initial database that contribute to the coverage in order to find a representative subset that satisfies the same coverage as the initial database. The approach is automated and efficiently executed against large databases and complex queries. The evaluation is carried out over two real life applications and a well-known database benchmark. The results show a very large degree of reduction as well as scalability in relation to the size of the initial database and the time needed to perform the reduction

Functional testing of applications that process the information stored in databases often requires a careful design of the test database. The larger the test database, the more difficult it is to develop and maintain tests as well as to load and reset the test data. This paper presents an approach to reduce a database with respect to a set of SQL queries and a coverage criterion. The reduction procedures search the rows in the initial database that contribute to the coverage in order to find a representative subset that satisfies the same coverage as the initial database. The approach is automated and efficiently executed against large databases and complex queries. The evaluation is carried out over two real life applications and a well-known database benchmark. The results show a very large degree of reduction as well as scalability in relation to the size of the initial database and the time needed to perform the reduction

URI:
http://hdl.handle.net/10651/36745
ISSN:
0098-5589
DOI:
10.1109/TSE.2016.2519032
Patrocinado por:

This work was supported in part by projects TIN2010-20057-C03-01 and TIN2013-46928-C3-1-R, funded by the Spanish Ministry of Economy and Competitiveness, and GRUPIN14-007, funded by the Principality of Asturias (Spain) and ERDF funds

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