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The city metaphor in software visualization: feelings, emotions, and thinking

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Abstract

Software visualization is a program comprehension technique used in the context of software maintenance, reverse engineering, and software evolution analysis. In the last decade, researchers have been exploring 3D representations for visualizing programs. Among these representations, one of the most popular is the city metaphor, which represents a target program as a city. Recently, this metaphor has been also implemented in interactive software visualization tools using Virtual Reality (VR) in an immersive 3D environment medium. We report the results of a study to assess the city metaphor implemented in a VR-based tool and in a 3D-based tool with respect to users’ feelings, emotions, and thinking. To this end, we contrasted these tools with a non-visual exploration tool (i.e., Eclipse). The main result of our study is: the use of the city metaphor implemented in a VR-based tool positively affects users’ feelings and emotions, while the thinking about this implementation is positive and comparable with that of a traditional 3D implementation of the city metaphor and it is slightly better than the thinking about a non-visual exploration tool (i.e., Eclipse).

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Notes

  1. The p-values returned by the Dunn’s test are adjusted according to the Bonferroni adjustment [7].

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Authors and Affiliations

  1. University of Bari, Bari, Italy

    Simone Romano

  2. University of Basilicata, Potenza, Italy

    Nicola Capece, Ugo Erra & Giuseppe Scanniello

  3. Università della Svizzera italiana (USI), Lugano, Switzerland

    Michele Lanza

Authors
  1. Simone Romano
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  2. Nicola Capece
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  3. Ugo Erra
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  4. Giuseppe Scanniello
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  5. Michele Lanza
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Correspondence to Giuseppe Scanniello.

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Appendices

Appendix A: Comprehension tasks

In this appendix, we report the comprehension tasks the participants had to carry out as well as the rationale behind them and the corresponding concerns (see Table 14). The description of these tasks is taken from the paper by Wettel et al. [40].

Table 14 Description of the comprehension tasks taken from the paper by Wettel et al. [40]
Full size table

Appendix B: Descriptive statistics

In this appendix, we provide the descriptive statistics values—mean, median, and SD (Standard Deviation). In particular, the descriptive statistics for the PAS and NAS values are shown in Table 15. These values are grouped by tool and kind of participants (i.e., all the participants or only the undergraduates). We do not report the descriptive statistics for the graduates because of their low number (three in the Code2City and Code2CityVR groups, respectively, while two in the Eclipse group). When comparing the results of all the participants with those of the undergraduates only, we can notice that there are not huge differences in terms of either PAS or NAS values. In particular, for Code2City and Eclipse the PAS values are, on average, slightly better when considering the undergraduates only. As for Code2CityVR, the PAS values are, on average, slightly better when considering all the participants. The NAS values are, whatever the tool was, slightly better when considering the undergraduates only. Summing up, we can observe no noticeable difference in the participants’ emotions and feelings when comparing all of them with the undergraduates only.

Table 15 Some descriptive statistics for PAS and NAS grouped by tool and kind of participants
Full size table

Similarly to Table 15, we show the descriptive statistics for TQ, IQ, SQ, P, PEU, PU, AU, and BIU in Table 16. We can observe that their distributions are not so different when considering either all the participants or the undergraduates only. In particular, for Code2City and Eclipse the TQ values are, on average, slightly better when considering the undergraduates only. As for Code2City, the values are slightly better when considering all the participants. A similar trend can be observed for IQ, SQ, P, PU, AU, and BIU. With respect to PEU, for both Code2CityVR and Eclipse groups the mean value is slightly better when considering all the participants (while the mean PEU value is slightly better for Code2City when considering the undergraduates only). Again, we can conclude that there is no noticeable difference in the thinking of the undergraduates with respect that of all the participants.

Table 16 Some descriptive statistics for TQ, IQ, SQ, P, PEU, PU, AU, and BIU grouped by tool and kind of participants
Full size table

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Romano, S., Capece, N., Erra, U. et al. The city metaphor in software visualization: feelings, emotions, and thinking. Multimed Tools Appl 78, 33113–33149 (2019). https://doi.org/10.1007/s11042-019-07748-1

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