Published August 8, 2024 | Version v1

Supplementary Material: Effectiveness of Performance Visualizations for Declarative Model Transformations

  • 1. ROR icon Chalmers University of Technology
  • 2. ROR icon University of Gothenburg
  • 3. ROR icon Universität Ulm

Description

We performed a case study to evaluate whether our performance visualizations developed for the declarative transformation language Henshin are suitable for performing a root cause analysis. Our study consisted of four parts. 1) Participants completed a questionnaire that collected data on their demographics and knowledge of model transformations. 2) The participants watched a video explaining the basics of models, Henshin, and our performance visualizations. 3) The study participants solved four different tasks one after the other. Guided by a questionnaire, they carried out a root cause analysis. 4) Finally, in a short interview session, we asked the participants about their assessment of the comprehensibility and usefulness of the visualizations.

In total, 18 participants took part in our study. Our results show that most participants could correctly read and interpret the information provided by the visualizations. The majority of our participants could propose a performance optimization based on the visualizations that optimized the execution of a transformation.

This data set contains our study material, which is necessary to repeat the study, our raw and processed data.

Notes

This work was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 358569332 and partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.

Files

Documentation.pdf

Files (119.7 MB)

Additional details

Related works

Continues
Conference paper: 10.1145/3578244.3583727 (DOI)