Social dogfood: A framework to minimise clouc field defects through crowd sourced testing

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.