A Multi-start Constructive Procedure for Test Case Generation in Model Transformation Testing

Abstract

Ensuring the correctness of model transformations is a critical concern in Model-Driven Engineering, as it directly conditions the reliability of the software development activities that depend on them. To validate the correctness of model transformation processes, it is necessary to have a representative and diverse set of input testing models. However, manually constructing such a set is costly and error-prone. In this work, we propose a multi-start constructive procedure for the automatic generation of test model sets. The method starts by building a trivial feasible model and then constructs new ones by applying different operators. By identifying the feasible region of the search space, the method is able to efficiently generate feasible models. The proposed method is evaluated in comparison to the state of the art on three families of instances of varying complexity, considering both unconstrained and constrained settings. Results show that the constructive procedure effectively constructs feasible high-quality models in low computing times, even for instances for which the state-the-art method is not able to find feasible solutions at all within the time limit.

Alejandro Aunión Ruiz

Artificial Intelligence Phd Student

Alejandro Aunión Ruiz holds a degree in Cybersecurity Engineering from Universidad Rey Juan Carlos. He is currently pursuing a Master’s in Research in Artificial Intelligence at Universidad Menéndez Pelayo.

Javier Yuste

Phd in Artificial Intelligence

Eduardo García Pardo

Full Professor

One of the founders of the investigation group GRAFO, whose main line of research is the development of algorithms to tackle optimization problems, the topic of the researcher’s Doctoral Thesis and which their most notable publications are framed.