Trace comprehension operators for executable DSLs

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Abstract

Recent approaches contribute facilities to breathe life into metamodels, thus making behavioral models directly executable. Such facilities are particularly helpful to better utilize a model over the time dimension, e.g., for early validation and verification. However, when even a small change is made to the model, to the language definition (e.g., semantic variation points), or to the external stimuli of an execution scenario, it remains difficult for a designer to grasp the impact of such a change on the resulting execution trace. This prevents accessible trade-off analysis and design-space exploration on behavioral models. In this paper, we propose a set of formally defined operators for analyzing execution traces. The operators include dynamic trace filtering, trace comparison with diff computation and visualization, and graph-based view extraction to analyze cycles. The operators are applied and validated on a demonstrative example that highlight their usefulness for the comprehension specific aspects of the underlying traces.

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Leroy, D., Bousse, E., Megna, A., Combemale, B., & Wimmer, M. (2018). Trace comprehension operators for executable DSLs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10890 LNCS, pp. 293–310). Springer Verlag. https://doi.org/10.1007/978-3-319-92997-2_19

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