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Gian-Luca Fuhrmann

dblp:345/1974 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution › program comprehension
code comprehension
0.712023
Developers' Visuo-spatial Mental Model and Program Comprehension · ICSE 2023
Software maintenance and evolution
program comprehension
0.712023
Developers' Visuo-spatial Mental Model and Program Comprehension · ICSE 2023
Visualization and visual analytics
software visualization
0.212023
Developers' Visuo-spatial Mental Model and Program Comprehension · ICSE 2023

Methods — techniques the papers use, named apart from their topics

corsi block test · 1.3between-subject experiment · 1.3
YearPublicationVenuePosition
2023 Developers' Visuo-spatial Mental Model and Program Comprehension
abstract
Previous works from research and industry have proposed a spatial representation of code in a canvas, arguing that a navigational code space confers developers the freedom to organise elements according to their understanding. By allowing developers to translate logical relatedness into spatial proximity, this code representation could aid in code navigation and comprehension. However, the association between developers' code comprehension and their visuo-spatial mental model of the code is not yet well understood. This mental model is affected on the one hand by the spatial code representation and on the other by the visuo-spatial working memory of developers. We address this knowledge gap by conducting an online experiment with 20 developers following a between-subject design. The control group used a conventional tab-based code visualization, while the experimental group used a code canvas to complete three code comprehension tasks. Furthermore, we measure the participants' visuo-spatial working memory using a Corsi Block test at the end of the tasks. Our results suggest that, overall, neither the spatial representation of code nor the visuo-spatial working memory of developers has a significant impact on comprehension performance. However, we identified significant differences in the time dedicated to different comprehension activities such as navigation, annotation, and UI interactions.
Abir Bouraffa, Gian-Luca Fuhrmann, Walid Maalej
ICSE2