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The Dagstuhl Beginners Guide to Reproducibility for Experimental Networking Research
Technical University of Munich, Germany.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7311-9334
Max Planck Society, Germany.
Technical University of Munich, Germany.
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2019 (English)In: Computer communication review, ISSN 0146-4833, E-ISSN 1943-5819, Vol. 49, no 1, p. 24-30Article in journal (Other academic) Published
Abstract [en]

Reproducibility is one of the key characteristics of good science, but hard to achieve for experimental disciplines like Internet measurements and networked systems. This guide provides advice to researchers, particularly those new to the field, on designing experiments so that their work is more likely to be reproducible and to serve as a foundation for follow-on work by others.

Place, publisher, year, edition, pages
New York: Association for Computing Machinery (ACM), 2019. Vol. 49, no 1, p. 24-30
Keywords [en]
Experimental networking research, Internet measurements, Reproducibility, Guidance
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-71721DOI: 10.1145/3314212.3314217ISI: 000460375100005OAI: oai:DiVA.org:kau-71721DiVA, id: diva2:1302640
Available from: 2019-04-05 Created: 2019-04-05 Last updated: 2019-04-10Bibliographically approved

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Brunström, Anna

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