Model transformation languages under a magnifying glass: a controlled experiment with Xtend, ATL, and QVT

Hebig, Regina; Seidl, Christoph; Berger, Thorsten; Pedersen, John Kook; Wąsowski, Andrzej

doi:10.1145/3236024.3236046

Cited by 14 publications

(7 citation statements)

References 36 publications

(39 reference statements)

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“…We believe that the credibility of research efforts on MTL can be greatly improved with studies that provide empirical substantiation to the speculated properties. Advances like those made by Hebig et al (2018) are rare and further ones, based on real world examples, must be carried out.…”

Section: Evaluation Of Mtl Capabilities and Propertiesmentioning

confidence: 99%

Advantages and disadvantages of (dedicated) model transformation languages

et al. 2022

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Context Model driven development envisages the use of model transformations to evolve models. Model transformation languages, developed for this task, are touted with many benefits over general purpose programming languages. However, a large number of these claims have not yet been substantiated. They are also made without the context necessary to be able to critically assess their merit or built meaningful empirical studies around them. Objective The objective of our work is to elicit the reasoning, influences and background knowledge that lead people to assume benefits or drawbacks of model transformation languages. Method We conducted a large-scale interview study involving 56 participants from research and industry. Interviewees were presented with claims about model transformation languages and were asked to provide reasons for their assessment thereof. We qualitatively analysed the responses to find factors that influence the properties of model transformation languages as well as explanations as to how exactly they do so. Results Our interviews show, that general purpose expressiveness of GPLs, domain specific capabilities of MTLs as well as tooling all have strong influences on how people view properties of model transformation languages. Moreover, the Choice of MTL, the Use Case for which a transformation should be developed as well as the Skill s of involved stakeholders have a moderating effect on the influences, by changing the context to consider. Conclusion There is a broad body of experience, that suggests positive and negative influences for properties of MTLs. Our data suggests, that much needs to be done in order to convey the viability of model transformation languages. Efforts to provide more empirical substance need to be undergone and lacklustre language capabilities and tooling need to be improved upon. We suggest several approaches for this that can be based on the results of the presented study.

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Section: Evaluation Of Mtl Capabilities and Propertiesmentioning

confidence: 99%

Advantages and disadvantages of (dedicated) model transformation languages

et al. 2022

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“…In fact, in our own research, we have implemented various model transformations using a GPL; examples of this include the meta-tooling facilities of established research tools like SiLift [8] and SERGe [9,10], or the implementation of model refactorings and model mutations in experimental setups of more recent empirical evaluations [11,12]. The presumption that model transformations can just as well be written in a GPL has been confirmed by a community discussion on the future of model transformation languages [7], and, at least partially, by an empirical study conducted by Hebig et al [13]. Our argumentation for specifying model transformations using a modern GPL is mainly rooted in the idea that new language features allow developers to heavily reduce the boilerplate code that MTLs claim to abstract away from.…”

Section: Context and Motivationmentioning

confidence: 99%

“…Hebig et al investigate the benefit of using specialized model transformation languages compared to general purpose languages by means of a controlled experiment where participants had to complete a comprehension task, a change task, and they had to write one transformation from scratch [13]. They compare ATL, QVT-O, and the GPL Xtend, and they found no clear evidence for an advantage when using MTLs.…”

Section: Related Workmentioning

confidence: 99%

Contrasting dedicated model transformation languages versus general purpose languages: a historical perspective on ATL versus Java based on complexity and size

2021

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Model transformations are among the key concepts of model-driven engineering (MDE), and dedicated model transformation languages (MTLs) emerged with the popularity of the MDE pssaradigm about 15 to 20 years ago. MTLs claim to increase the ease of development of model transformations by abstracting from recurring transformation aspects and hiding complex semantics behind a simple and intuitive syntax. Nonetheless, MTLs are rarely adopted in practice, there is still no empirical evidence for the claim of easier development, and the argument of abstraction deserves a fresh look in the light of modern general purpose languages (GPLs) which have undergone a significant evolution in the last two decades. In this paper, we report about a study in which we compare the complexity and size of model transformations written in three different languages, namely (i) the Atlas Transformation Language (ATL), (ii) Java SE5 (2004–2009), and (iii) Java SE14 (2020); the Java transformations are derived from an ATL specification using a translation schema we developed for our study. In a nutshell, we found that some of the new features in Java SE14 compared to Java SE5 help to significantly reduce the complexity of transformations written in Java by as much as 45%. At the same time, however, the relative amount of complexity that stems from aspects that ATL can hide from the developer, which is about 40% of the total complexity, stays about the same. Furthermore we discovered that while transformation code in Java SE14 requires up to 25% less lines of code, the number of words written in both versions stays about the same. And while the written number of words stays about the same their distribution throughout the code changes significantly. Based on these results, we discuss the concrete advancements in newer Java versions. We also discuss to which extent new language advancements justify writing transformations in a general purpose language rather than a dedicated transformation language. We further indicate potential avenues for future research on the comparison of MTLs and GPLs in a model transformation context.

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“…We dropped the terms advantage and disadvantage after initial searches, because they resulted in a too narrow of a result set which excluded key publications [29,33] manually identified by the authors.…”

Section: Search Strategymentioning

confidence: 99%

Claimed advantages and disadvantages of (dedicated) model transformation languages: a systematic literature review

2020

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There exists a plethora of claims about the advantages and disadvantages of model transformation languages compared to general-purpose programming languages. With this work, we aim to create an overview over these claims in the literature and systematize evidence thereof. For this purpose, we conducted a systematic literature review by following a systematic process for searching and selecting relevant publications and extracting data. We selected a total of 58 publications, categorized claims about model transformation languages into 14 separate groups and conceived a representation to track claims and evidence through the literature. From our results, we conclude that: (i) the current literature claims many advantages of model transformation languages but also points towards certain deficits and (ii) there is insufficient evidence for claimed advantages and disadvantages and (iii) there is a lack of research interest into the verification of claims.

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Model transformation languages under a magnifying glass: a controlled experiment with Xtend, ATL, and QVT

Cited by 14 publications

References 36 publications

Advantages and disadvantages of (dedicated) model transformation languages

Advantages and disadvantages of (dedicated) model transformation languages

Contrasting dedicated model transformation languages versus general purpose languages: a historical perspective on ATL versus Java based on complexity and size

Claimed advantages and disadvantages of (dedicated) model transformation languages: a systematic literature review

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