2026-05-30T17:20:32Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/120902026-02-03T12:18:01Zcom_10630_2254col_10630_37959

Generating Effective Test Suites for Model Transformations Using Classifying Terms Vallecillo-Moreno, Antonio Jesús Hilken, Frank Burgueño-Caballero, Lola Gogolla, Martin Soporte lógico Ingeniería del software Generating sample models for testing a model transformation is no easy task. This paper explores the use of classifying terms and stratified sampling for developing richer test cases for model transformations. Classifying terms are used to define the equivalence classes that characterize the relevant subgroups for the test cases. From each equivalence class of object models, several representative models are chosen depending on the required sample size. We compare our results with test suites developed using random sampling, and conclude that by using an ordered and stratified approach the coverage and effectiveness of the test suite can be significantly improved. 2016-09-27T09:00:34Z 2016-09-27T09:00:34Z 2016 2016-09-27 conference output http://hdl.handle.net/10630/12090 eng VOLT @ MODELS, 2016 Saint-Malo, Francia Octubre de 2016 open access by-nc-nd