RT Journal Article
T1 Model Transformation Testing and Debugging: A Survey
A1 Troya-Castilla, Javier
A1 Segura, Sergio
A1 Burgueño-Caballero, Lola
A1 Wimmer, Manuel
K1 Ingeniería del software
K1 Soporte lógico de sistemas
AB Model transformations are the key technique in Model-Driven Engineering (MDE) to manipulate and construct models. As a consequence, the correctness of software systems built with MDE approaches relies mainly on the correctness of model transformations, and thus, detecting and locating bugs in model transformations have been popular research topics in recent years. This surge of work has led to a vast literature on model transformation testing and debugging, which makes it challenging to gain a comprehensive view of the current state of the art. This is an obstacle for newcomers to this topic and MDE practitioners to apply these approaches. This paper presents a survey on testing and debugging model transformations based on the analysis of \nPapers~papers on the topics. We explore the trends, advances, and evolution over the years, bringing together previously disparate streams of work and providing a comprehensive view of these thriving areas. In addition, we present a conceptual framework to understand and categorise the different proposals. Finally, we identify several open research challenges and propose specific action points for the model transformation community.
PB ACM
YR 2022
FD 2022
LK https://hdl.handle.net/10630/23891
UL https://hdl.handle.net/10630/23891
LA eng
NO Javier Troya, Sergio Segura, Lola Burgueño, and Manuel Wimmer. 2022. Model Transformation Testing and Debugging: A Survey. ACM Comput. Surv. Just Accepted (February 2022). DOI:https://doi.org/10.1145/3523056
NO This work is partially supported by the European Commission (FEDER) and Junta de Andalucia under projects APOLO (US-1264651) andEKIPMENT-PLUS (P18-FR-2895), by the Spanish Government (FEDER/Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación) under projects HORATIO (RTI2018-101204-B-C21), COSCA (PGC2018-094905-B-I00) and LOCOSS (PID2020-114615RB-I00), by the Austrian Science Fund (P 28519-N31, P 30525-N31), and by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development (CDG)
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026