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    Social dogfood: A Framework to minimise Cloud field defects through crowd sourced testing


    Dunne, Jonathan and Malone, David (2017) Social dogfood: A Framework to minimise Cloud field defects through crowd sourced testing. In: 2017 28th Irish Signals and Systems Conference (ISSC), 20-21 June 2017, Killarney, Ireland.

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    Abstract

    Delivering software for the Cloud represents a challenge for both micro teams and Small Medium Enterprises (SMEs), in part due to the rapid release methods adopted and the numerous ways in which software defects can be detected. We study field defect detection rates in a framework where these rates are used to refocus in-house test resources. Using an enterprise dataset, we address the question of what types of defects are found in the field and how soon after a system goes live defects are detected. Our framework can aid both micro teams and SMEs to minimise the number of defects found in the field by maximising internal usage through 'Dogfood' programs and by leveraging crowdsourced test methodologies.

    Item Type: Conference or Workshop Item (Paper)
    Additional Information: This is the preprint version of the published paper, which is available at DOI: 10.1109/ISSC.2017.7983605
    Keywords: social dogfood; cloud field defects; crowd sourced testing; small medium enterprises; SMEs; software defects; field defect detection rates; in-house test resources; Dogfood programs;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 10054
    Depositing User: Dr. David Malone
    Date Deposited: 04 Oct 2018 13:37
    Refereed: Yes
    URI:

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