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Dedicated model transformation languages are claimed to provide many benefitsover the use of general purpose languages for developing model transformations.However, the actual advantages associated with the use of MTLs are poorlyunderstood empirically. There is little knowledge and empirical assessmentabout what advantages and disadvantages hold and where they originate from. Ina prior interview study, we elicited expert opinions on what advantages resultfrom what factors and a number of factors that moderate the influence. We aimto quantitatively asses the interview results to confirm or reject the effectsposed by different factors. We intend to gain insights into how valuabledifferent factors are so that future studies can draw on these data fordesigning targeted and relevant studies. We gather data on the factors andquality attributes using an online survey. To analyse the data, we useuniversal structure modelling based on a structure model. We use significancevalues and path coefficients produced bz USM for each hypothesisedinterdependence to confirm or reject correlation and to weigh the strength ofinfluence present. We analyzed 113 responses. The results show that the Tracingand Reuse Mechanisms are most important overall. Though the observed effectswere generally 10 times lower than anticipated. Additionally, we found that amore nuanced view of moderation effects is warranted. Their moderatinginfluence differed significantly between the different influences, with thestrongest effects being 1000 times higher than the weakest. The empiricalassessment of MTLs is a complex topic that cannot be solved by looking at asingle stand-alone factor. Our results provide clear indication that evaluationshould consider transformations of different sizes and use-cases. Languagedevelopment should focus on providing transformation specific reuse mechanisms .

Traceability and Reuse Mechanisms, the most important Properties of Model Transformation Languages