Test Selection with Moose In Industry - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2016

Test Selection with Moose In Industry

Impact of Granularity


Automatic testing constitutes an important part of everyday development practice. Worldline, a major IT company, is creating more and more tests to ensure the good behaviour of its applications and gain in efficiency and quality. But running all these tests may take hours. For this reason tests are not launched as often as they should and are mostly run at night. The company wishes to improve its development and testing process by giving to developers rapid feedback after a change. An interesting solution is to reduce the number of tests to run by identifying only those exercising the piece of code changed. Two main approaches are proposed in the literature: static and dynamic. The static approach creates a model of the source code and explores it to find links between changed methods and tests. The dynamic approach records invocations of methods during the execution of test scenarios. Moose, a tool allowing to create static models of source code is a good candidate to carry this approach. Thanks to the partnership created with Worldline, we investigate on three industrial, closed source, cases to compare static and dynamic approaches. We evaluate the impact on the results of the frequency of modification of methods or considering groups of methods instead of single ones. We found that considering commits instead of individual methods tends to worsen the results, perhaps due to their large size.
Fichier principal
Vignette du fichier
Test_Selection_with_Moose_In_Industry.pdf (180.8 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01352468 , version 1 (08-08-2016)



Vincent Blondeau, Nicolas Anquetil, Stéphane Ducasse, Sylvain Cresson, Pascal Croisy. Test Selection with Moose In Industry. IWST'16, Aug 2016, Prague, Czech Republic. ⟨10.1145/2991041.2991058⟩. ⟨hal-01352468⟩
201 View
143 Download



Gmail Facebook X LinkedIn More