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Daniel Prett Campagna

dblp:290/4520 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-5313-207XORCID · reported

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
Empirical software engineering · 81% Services computing and microservices · 19%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
interactive data exploration
0.612022
Dominoes: An Interactive Exploratory Data Analysis Tool for Software Relationships · IEEE Trans. Software Eng. 2022
Empirical software engineering
mining software repositories
0.612022
Dominoes: An Interactive Exploratory Data Analysis Tool for Software Relationships · IEEE Trans. Software Eng. 2022
Empirical software engineering
developer studies
0.212022
Dominoes: An Interactive Exploratory Data Analysis Tool for Software Relationships · IEEE Trans. Software Eng. 2022
Services computing and microservices › workflow management
task assignment
0.212022
Dominoes: An Interactive Exploratory Data Analysis Tool for Software Relationships · IEEE Trans. Software Eng. 2022

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

scenario-based evaluation · 1.1interactive visualization · 1.1
YearPublicationVenuePosition
2022 Dominoes: An Interactive Exploratory Data Analysis Tool for Software Relationships
abstract
Project comprehension questions, such as “which modified artifacts can affect my work?” and “how can I identify the developers who should be assigned to a given task?” are difficult to answer, require an analysis of the project and its data, are context specific, and cannot always be pre-defined. Current research approaches are restricted to post hoc analyses over software repositories. Very few interactive exploratory tools exist since the large amount of data that need to be analyzed prohibits its exploration at interactive rates. Moreover, such analyses typically require the user to create complex scripts or queries to extract the desired information from data. Here we present Dominoes, a tool for interactive data exploration aimed at end users (i.e., project managers or developers). Dominoes allows users to interact with different types and units of data to investigate project relationships and view intermediate results as charts, tables, and graphs. Additionally, it allows users to save the derived data as well as their exploration paths for later use. In a scenario-based evaluation study, participants achieved a success rate of 86 percent in their explorations, with a mean time of 7.25 minutes for answering a set of (project) exploration questions.
Jose Ricardo da Silva Jr., Daniel Prett Campagna, Esteban Walter Gonzalez Clua, Anita Sarma, Leonardo Murta 0001
IEEE Trans. Software Eng.2