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dc.contributor.authorCanini, Marco
dc.contributor.authorCrowcroft, Jon
dc.date.accessioned2017-10-03T12:49:36Z
dc.date.available2017-10-03T12:49:36Z
dc.date.issued2017-08-10
dc.identifier.citationCanini M, Crowcroft J (2017) Learning Reproducibility with a Yearly Networking Contest. Proceedings of the Reproducibility Workshop on ZZZ - Reproducibility ’17. Available: http://dx.doi.org/10.1145/3097766.3097769.
dc.identifier.doi10.1145/3097766.3097769
dc.identifier.urihttp://hdl.handle.net/10754/625733
dc.description.abstractBetter reproducibility of networking research results is currently a major goal that the academic community is striving towards. This position paper makes the case that improving the extent and pervasiveness of reproducible research can be greatly fostered by organizing a yearly international contest. We argue that holding a contest undertaken by a plurality of students will have benefits that are two-fold. First, it will promote hands-on learning of skills that are helpful in producing artifacts at the replicable-research level. Second, it will advance the best practices regarding environments, testbeds, and tools that will aid the tasks of reproducibility evaluation committees by and large.
dc.description.sponsorshipWe thank our shepherd, Bob Lantz and the reviewers for their feedback. We are thankful to Olivier Bonaventure, Luigi Iannone, David Keyes, Shriram Krishnamurthi, Jennifer Rexford, Robert Ricci, Damien Saucez, Matthias Waehlisch, and Keith Winstein for sharing useful references and giving us suggestions and support for this paper.
dc.publisherACM Press
dc.relation.urlhttp://dl.acm.org/citation.cfm?doid=3097766.3097769
dc.subjectReproducible research
dc.subjectGamification
dc.subjectDesign contest
dc.titleLearning Reproducibility with a Yearly Networking Contest
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.identifier.journalProceedings of the Reproducibility Workshop on ZZZ - Reproducibility '17
dc.contributor.institutionUniversity of Cambridge
kaust.personCanini, Marco


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