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Efficient and scalable omniscient debugging for model transformations

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Abstract

This paper discusses a technique for supporting omniscient debugging for model transformations, which are used to define core operations on software and system models. Similar to software systems developed using general-purpose languages, model transformations are also subject to human error and may possess defects. Existing model-driven engineering tools provide stepwise execution to aid developers in locating and removing defects. In this paper, we describe our investigation into a technique and associated algorithms that support omniscient debugging features for model transformations. Omniscient debugging enables enhanced navigation and exploration features during a debugging session beyond those possible in a strictly stepwise execution environment. Finally, the execution time performance is comparatively evaluated against stepwise execution, and the scalability (in terms of memory usage) is empirically investigated.

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Notes

  1. http://wiki.eclipse.org/ATL/User_Guide_-_The_ATL_Language#ATL_Helpers.

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Authors and Affiliations

  1. Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA

    Jonathan Corley & Jeff Gray

  2. Department of Computer Science, University of West Florida, Pensacola, FL, USA

    Brian P. Eddy

  3. Department of Computer Science, University of Montreal, Montreal, Canada

    Eugene Syriani

Authors
  1. Jonathan Corley
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  2. Brian P. Eddy
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  3. Eugene Syriani
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  4. Jeff Gray
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Correspondence to Jonathan Corley.

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Corley, J., Eddy, B.P., Syriani, E. et al. Efficient and scalable omniscient debugging for model transformations. Software Qual J 25, 7–48 (2017). https://doi.org/10.1007/s11219-015-9304-4

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