Paper Info
Title
Model transformation languages under a magnifying glass: a controlled experiment with Xtend, ATL, and QVT.
Abstract
In Model-Driven Software Development, models are automatically processed 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 over 78 subjects solve 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). Our results 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.
Year
DOI
Venue
2019
10.1145/3236024.3236046
ESEC/SIGSOFT FSE
Keywords
DocType
ISBN
Model Transformation Languages,Experiment,Xtend,ATL,QVT
Conference
978-1-4503-5573-5
Citations 
PageRank 
References 
1
0.35
20
Authors
5
Name
Order
Citations
PageRank
Regina Hebig117924.24
Christoph Seidl220720.15
Thorsten Berger360334.35
John Kook Pedersen410.35
Andrzej Wasowski5128260.47