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Model Transformation Languages under a Magnifying Glass: A Controlled Experiment with Xtend, ATL, and QVT

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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 languageEnglish
Title of host publicationSoftware Engineering and Software Management, SE/SWM 2019, Stuttgart, Germany, February 18-22, 2019
PublisherGesellschaft fur Informatik (GI)
Publication date2019
Pages91-92
ISBN (Electronic)978-3-88579-686-2
DOIs
Publication statusPublished - 2019
EventSoftware Engineering and Software Management - , Germany
Duration: 1 Jan 2019 → …

Conference

ConferenceSoftware Engineering and Software Management
LandGermany
Periode01/01/2019 → …
SeriesLecture Notes in Informatics
ISSN1617-5468

ID: 84784469