ParVis

Costagliola, Gennaro; Rosa, Mattia De; Fuccella, Vittorio; Minas, Mark

doi:10.1145/3399715.3399853

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…6) the partial derivation trees identified by the parser so far are displayed as a parse forest. 5 The roots of these trees correspond to the edge labels in the GSS. However, this correspondence is not permanently visualized in order not to overload the display.…”

Section: Gpsrmentioning

confidence: 99%

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Visual exploration of visual parser execution

Costagliola

Rosa

Fuccella

et al. 2021

Multimed Tools Appl

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In this paper, we present ParVis, an interactive visual system for the animated visualization of logged parser trace executions. The system allows a parser implementer to create a visualizer for generated parsers by simply defining a JavaScript module that maps each logged parser instruction into a set of events driving the visual system interface. The result is a set of interacting graphical/text windows that allows users to explore logged parser executions and helps them to have a complete understanding of how the parser behaves during its execution on a given input. We used our system to visualize the behavior of textual as well as visual parsers and describe here two of these uses. Moreover, in order to validate the efficacy of our system, we ran a user experiment where students analyzed a CUP-generated parser both with ParVis, instantiated to LALR parsers, and the standard CUP debug facilities. The results show that students can indeed analyze parser behavior and find mistakes in parser specifications more easily and quickly using ParVis. In particular, in some parser design tasks, using ParVis participants achieved a higher success rate of 50% in 42% less time with respect to the baseline system.

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Section: Gpsrmentioning

confidence: 99%

“…This work is an extension of [5]. The new contribution consists of the GPSR PARVIS instance described in Section 3.2 and the user experiment described in Sections 4 and 5.…”

Section: Introductionmentioning

confidence: 99%