Model Transformation Languages under a Magnifying Glass: A Controlled Experiment with Xtend, ATL, and QVT
Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
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.
Original language | English |
---|---|
Title of host publication | Software Engineering and Software Management, SE/SWM 2019, Stuttgart, Germany, February 18-22, 2019 |
Publisher | Gesellschaft fur Informatik (GI) |
Publication date | 2019 |
Pages | 91-92 |
ISBN (Electronic) | 978-3-88579-686-2 |
DOIs | |
Publication status | Published - 2019 |
Event | Software Engineering and Software Management - , Germany Duration: 1 Jan 2019 → … |
Conference
Conference | Software Engineering and Software Management |
---|---|
Land | Germany |
Periode | 01/01/2019 → … |
Series | Lecture Notes in Informatics |
---|---|
ISSN | 1617-5468 |
Downloads
No data available
ID: 84784469