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    Learning Reproducibility with a Yearly Networking Contest

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    Type
    Conference Paper
    Authors
    Canini, Marco cc
    Crowcroft, Jon
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computer Science Program
    Date
    2017-08-10
    Online Publication Date
    2017-08-10
    Print Publication Date
    2017
    Permanent link to this record
    http://hdl.handle.net/10754/625733
    
    Metadata
    Show full item record
    Abstract
    Better 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.
    Citation
    Canini 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.
    Sponsors
    We 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.
    Publisher
    Association for Computing Machinery (ACM)
    Journal
    Proceedings of the Reproducibility Workshop on ZZZ - Reproducibility '17
    DOI
    10.1145/3097766.3097769
    Additional Links
    http://dl.acm.org/citation.cfm?doid=3097766.3097769
    ae974a485f413a2113503eed53cd6c53
    10.1145/3097766.3097769
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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