VLDB 2026 Research / reviewers in the wild / expert
Maryi Arciniegas-Mendez
dblp:166/1000
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 first-author
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 · 56% Software maintenance and evolution · 44% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
collaborative software development |
0.3 | 1 | 2017 | Using the Model of Regulation to Understand Software Development Collaboration Practices and Tool Support · CSCW 2017 |
Methods — techniques the papers use, named apart from their topics
model of regulation · 0.3interview study · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Using the Model of Regulation to Understand Software Development Collaboration Practices and Tool SupportabstractWe developed the Model of Regulation to provide a vocabulary for comparing and analyzing collaboration practices and tools in software engineering. This paper discusses the model's ability to capture how individuals self-regulate their own tasks and activities, how they regulate one another, and how they achieve a shared understanding of project goals and tasks. Using the model, we created an "action-oriented" instrument that individuals, teams, and organizations can use to reflect on how they regulate their work and on the various tools they use as part of regulation. We applied this instrument to two industrial software projects, interviewing one or two stakeholders from each project. The model allowed us to identify where certain processes and communication channels worked well, while recognizing friction points, communication breakdowns, and regulation gaps. We believe this model also shows potential for application in other domains. Maryi Arciniegas-Mendez |
CSCW | 1 |