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End-to-end model-transformation comprehension through fine-grained traceability information

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Abstract

The construction and maintenance of model-to-model and model-to-text transformations pose numerous challenges to novice and expert developers. A key challenge involves tracing dependency relationships between artifacts of a transformation ecosystem. This is required to assess the impact of metamodel evolution, to determine metamodel coverage, and to debug complex transformation expressions. This paper presents an empirical study that investigates the performance of developers reflecting on the execution semantics of model-to-model and model-to-text transformations. We measured the accuracy and efficiency of 25 developers completing a variety of traceability-driven tasks in two model-based code generators. We compared the performance of developers using ChainTracker, a traceability analysis environment developed by our team, and that of developers using Eclipse Modeling. We present statistically significant evidence that ChainTracker improves the performance of developers reflecting on the execution semantics of transformation ecosystems. We discuss how developers supported by off-the-shelf development environments are unable to effectively identify dependency relationships in nontrivial model-transformation chains.

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Notes

  1. http://goo.gl/YcWHNX.

  2. Multiple examples of parallel-coordinate visualizations are available at https://syntagmatic.github.io/parallel-coordinates/.

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Acknowledgements

This work was supported by The Killam Trust, NSERC (the Discovery and the IRC program), the GRAND NCE and IBM Canada. The development of PhyDSL was supported by the AGE-WELL NCE. We would like to thank Kelsey Gaboriau and Vina Nguyen for their support during the development of ChainTracker. We would also like to thank Kelly Garces for her generous help during the execution of this study.

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Authors and Affiliations

  1. Department of Computing Science, University of Alberta, Edmonton, AB, Canada

    Victor Guana & Eleni Stroulia

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  1. Victor Guana
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  2. Eleni Stroulia
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Correspondence to Victor Guana.

Additional information

Communicated by Prof. Lionel Briand.

Appendices

Appendix A: Questionnaires

See Tables 3 and 4.

Table 3 Session A: ScreenFlow Questionnaire
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Table 4 Session B: PhyDSL Questionnaire
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Appendix B: Result tables

See Tables 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and 18.

figure j
Table 5 Session A (ScreenFlow)—results: determining metamodel coverage and expression location
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Table 6 Session B (PhyDSL)—results: determining metamodel coverage and expression location
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Table 7 Session A (ScreenFlow)—results: identifying metamodel dependencies in M2M transformations (element level)
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Table 8 Session B (PhyDSL)—results: identifying metamodel dependencies in M2M transformations (element level)
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Table 9 Session A (ScreenFlow)—results: identifying metamodel dependencies in single M2M transformations (property level)
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Table 10 Session B (PhyDSL)—results: identifying metamodel dependencies in M2M transformations (property level)
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Table 11 Session A (ScreenFlow)—results: identifying metamodel dependencies in M2T transformations
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Table 12 Session B (PhyDSL)—results: identifying metamodel dependencies in M2T transformations
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Table 13 Session A (ScreenFlow)—results: identifying generation dependencies in M2T transformations
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Table 14 Session B (PhyDSL)—results: identifying generation dependencies in M2T transformations
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Table 15 Session A (ScreenFlow)—results: identifying generation dependencies in MTCs (element level)
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Table 16 Session B (PhyDSL)—results: identifying generation dependencies in MTCs (element level)
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Table 17 Session A (ScreenFlow)—results: identifying generation dependencies in MTCs (property level)
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Table 18 Session B (PhyDSL)—results: identifying generation dependencies in MTCs (property level)
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Guana, V., Stroulia, E. End-to-end model-transformation comprehension through fine-grained traceability information. Softw Syst Model 18, 1305–1344 (2019). https://doi.org/10.1007/s10270-017-0602-0

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