TY - JOUR
T1 - The dagstuhl beginners guide to reproducibility for experimental networking research
AU - Bajpai, Vaibhav
AU - Kellerer, Wolfgang
AU - Smaragdakis, Georgios
AU - Brunstrom, Anna
AU - Pras, Aiko
AU - Wählisch, Matthias
AU - Feldmann, Anja
AU - Schulzrinne, Henning
AU - Wehrle, Klaus
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery. All Rights Reserved.
PY - 2019/1
Y1 - 2019/1
N2 - 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.
AB - 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.
KW - Experimental networking research
KW - Guidance
KW - Internet measurements
KW - Reproducibility
UR - http://www.scopus.com/inward/record.url?scp=85062355966&partnerID=8YFLogxK
U2 - 10.1145/3314212.3314217
DO - 10.1145/3314212.3314217
M3 - Article
AN - SCOPUS:85062355966
SN - 0146-4833
VL - 49
SP - 24
EP - 30
JO - Computer Communication Review
JF - Computer Communication Review
IS - 1
ER -