RT Journal Article
T1 Ant-colony optimization for automating test model generation in model transformation testing.
A1 Karimi, Meysam
A1 Kolahdouz-Rahimi, Shekoufeh
A1 Troya-Castilla, Javier
K1 Algoritmos computacionales
K1 Investigación operativa
K1 Optimización combinatoria
K1 Ingeniería del software
AB In model transformation (MT) testing, test data generation is of key importance. However, test suites are not available out of the box, and existing approaches to generate them require to provide not only the metamodel to which the models must conform, but some other domain-specific artifacts. For instance, an MT developer aiming to perform an incremental implementation of an MT may need to count on a quality test suite from the very beginning, even before all MT requirements are clear, only having the metamodels as input. We propose a black-box approach for the generation of test models where only the input metamodel of the MT is available. We propose an Ant-Colony Optimization algorithm for the search of test models satisfying the objectives of maximizing internal diversity and maximizing external diversity. We provide a tool prototype that implements this approach and generates the models in the well-established XMI interchange format. A comparison study with state-of-the-art frameworks shows that models are generated in reasonable times with low memory consumption. We empirically demonstrate the adequacy of our approach to generate effective test models, obtaining an overall mutation score above 80% from an evaluation with more than 5000 MT mutants.
PB Elsevier
YR 2023
FD 2023-11-04
LK https://hdl.handle.net/10630/27976
UL https://hdl.handle.net/10630/27976
LA eng
NO Meysam Karimi, Shekoufeh Kolahdouz-Rahimi, Javier Troya, Ant-colony optimization for automating test model generation in model transformation testing, Journal of Systems and Software, 2023, 111882, ISSN 0164-1212, https://doi.org/10.1016/j.jss.2023.111882
NO TED2021-130523B-I00PID2021-125527NB-I00
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026