An exploratory study on performance engineering in model transformations

Groner, Raffaela; Beaucamp, Luis; Tichy, Matthias; Becker, Steffen

doi:10.1145/3365438.3410950

Cited by 6 publications

(20 citation statements)

References 40 publications

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“…This paper complements our recent paper (Groner et al 2020a) that qualitatively investigates how developers deal with the performance of model transformation executions. In contrast to our work, most existing research on the performance of model transformations focuses on improving the engine executing the model transformations, e.g., by improving the application sequence of model transformation rules inside the engine (Fritsche et al 2017;Fleck et al 2015) or using parallel and/or concurrent execution engines (Sanchez Cuadrado et al 2020;Benelallam et al 2016).…”

Section: Introductionmentioning

confidence: 66%

“…In Tables 1 to 5, we marked the affected questions with an " * " after their ID. The complete questionnaire is available at (Groner et al 2021(Groner et al , 2020b.…”

Section: (E) Atl Profilermentioning

confidence: 99%

“…The procedure of our SLR is based on a review protocol template from Booth et al (2016). We searched for publications in the IEEE Xplore Digital Library and the ACM Digital Library, as they offer conference proceedings from several conferences on models and model transformations, such as MODELS, MODELSWARD, MiSE, or MoDeVVA (Groner et al 2021(Groner et al , 2020a.…”

Section: Participantsmentioning

confidence: 99%

“…In order to find potential participants with sufficient knowledge about model transformations, we looked for publications dealing with the model transformation languages ATL, Henshin, QVTo, or Viatra. We chose these languages for the following reasons: 1) The Eclipse plug-in of ATL (Piers 2010) provides a profiler at the transformation level and offers appropriate support, 2) Henshin is a representative for a purely declarative language, 3) QVTo is widely used and is standardized by Object Management Group (OMG) (2016) and 4) the Viatra engine already provides many different concepts that improve the performance of a transformation (D. Varró et al 2016) (Groner et al 2020a).…”

Section: Participantsmentioning

confidence: 99%

“…For QVTo, publications since 2007 were considered, as the Borland (Kurtev 2008) QVTo engine became available in 2007, which is later used as the QVTo engine in Eclipse. Our search for participants was split into two SLRs, one focused on publications about ATL, Henshin, and Viatra until 8th July 2019 and the other focused on publications about QVTo until 19th August 2019 (Groner et al 2021(Groner et al , 2020a.…”

Section: Participantsmentioning

confidence: 99%

See 4 more Smart Citations

A Survey on the Relevance of the Performance of Model Transformations.

Groner¹,

Juhnke²,

Götz³

et al. 2021

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In Model-Driven Engineering (MDE) model transformation languages are used to describe important operations on models.Such domain-specific languages are specially developed to describe transformation rules, according to which an output model should be generated from an input model. In comparison to these domain-specific languages, techniques to analyze and improve the performance of programs written in a general-purpose language, such as Java or C, are well known. However, are such techniques also needed for model transformation languages? Problem. Since these languages are only used in certain domains; the first question is whether performance is at all relevant for model transformations and whether techniques similar to those used to analyze and improve the performance of general-purpose languages are needed. Research in the performance of model transformations focuses mainly on comparing the performance of different languages or different definition styles or optimizing the engine that executes the transformation. However, it is not clear to what extent these efforts can mitigate or prevent performance issues, and there is also a lack of studies that examine to what extend the performance of transformations is relevant. Method. In order to close this gap and to answer the initial question about the relevance of performance, we conducted an online survey. For this purpose, we developed a questionnaire and identified 649 authors as potential participants based on a Systematic Literature Review (SLR) on a selection of model transformation languages. Additionally, we were able to acquire four further potential participants by advertising our study. In total, 84 participants took part in our survey. We used statistical tests such as Kendall's τ c , the Kruskal-Wallis-Test and the Mann-Whitney-U-Test to evaluate our hypotheses on relevant factors for the performance of model transformations. Results. The results show that specific performance is desired and that there is a willingness to improve performance. In this regard, we identified a need for insights necessary to better understand how a transformation is performed in order to be able to improve its performance. Furthermore, we investigated with the help of hypotheses tests the possible influencing factors that cause participants to try to analyze or improve the performance of model transformations. The main results of the hypotheses tests are that the satisfaction with the execution time, the size of the models used, the relevance of whether a specific execution time is not exceeded in the average case, and the knowledge of how a transformation engine executes a transformation are relevant factors.

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Section: Introductionmentioning

confidence: 66%

“…In Tables 1 to 5, we marked the affected questions with an " * " after their ID. The complete questionnaire is available at (Groner et al 2021(Groner et al , 2020b.…”

Section: (E) Atl Profilermentioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

See 3 more Smart Citations

A Survey on the Relevance of the Performance of Model Transformations.

Groner¹,

Juhnke²,

Götz³

et al. 2021

JOT

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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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