TY - GEN
T1 - Model Transformation Languages under a Magnifying Glass: A Controlled Experiment with Xtend, ATL, and QVT
AU - Hebig, Regina
AU - Seidl, Christoph
AU - Berger, Thorsten
AU - Kook Pedersen, John
AU - Wasowski, Andrzej
PY - 2019
Y1 - 2019
N2 - In Model-Driven Software Development, models are processed automatically to support the creation, build, and execution of systems. A large variety of dedicated model-transformation languages exists, promising to efficiently realize the automated processing of models. To investigate the actual benefit of using such specialized languages, we performed a large-scale controlled experiment in which 78 subjects solved 231 individual tasks using three languages. The experiment sheds light on commonalities and differences between model transformation languages (ATL, QVT-O) and on benefits of using them in common development tasks (comprehension, change, and creation) against a modern general-purpose language (Xtend). The results of our experiment show no statistically significant benefit of using a dedicated transformation language over a modern general-purpose language. However, we were able to identify several aspects of transformation programming where domain-specific transformation languages do appear to help, including copying objects, context identification, and conditioning the computation on types.
AB - In Model-Driven Software Development, models are processed automatically to support the creation, build, and execution of systems. A large variety of dedicated model-transformation languages exists, promising to efficiently realize the automated processing of models. To investigate the actual benefit of using such specialized languages, we performed a large-scale controlled experiment in which 78 subjects solved 231 individual tasks using three languages. The experiment sheds light on commonalities and differences between model transformation languages (ATL, QVT-O) and on benefits of using them in common development tasks (comprehension, change, and creation) against a modern general-purpose language (Xtend). The results of our experiment show no statistically significant benefit of using a dedicated transformation language over a modern general-purpose language. However, we were able to identify several aspects of transformation programming where domain-specific transformation languages do appear to help, including copying objects, context identification, and conditioning the computation on types.
KW - Model-Driven Software Development
KW - Model Transformation Languages
KW - Controlled Experiment
KW - ATL
KW - QVT-O
KW - General-Purpose Language
KW - Xtend
KW - Transformation Programming
KW - Comprehension Tasks
KW - Domain-Specific Languages
KW - Model-Driven Software Development
KW - Model Transformation Languages
KW - Controlled Experiment
KW - ATL
KW - QVT-O
KW - General-Purpose Language
KW - Xtend
KW - Transformation Programming
KW - Comprehension Tasks
KW - Domain-Specific Languages
U2 - 10.18420/se2019-25
DO - 10.18420/se2019-25
M3 - Article in proceedings
T3 - Lecture Notes in Informatics
SP - 91
EP - 92
BT - Software Engineering and Software Management, SE/SWM 2019, Stuttgart, Germany, February 18-22, 2019
PB - Gesellschaft fur Informatik (GI)
T2 - Software Engineering and Software Management
Y2 - 1 January 2019
ER -