Dione: an integrated measurement and defect prediction solution

Authors:
Bora Caglayan;Ayse Tosun Misirli;Gul Calikli;Ayse Bener;Turgay Aytac;Burak Turhan
Affiliations:
Bogazici University, Turkey;University of Oulu, Finland;Bogazici University, Turkey;Ryerson University, Toronto, CA;Prescience Inc.;University of Oulu, Finland
Venue:
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
Year:
2012

Citing 2
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Practical considerations in deploying statistical methods for defect prediction: A case study within the Turkish telecommunications industry

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Abstract

We present an integrated measurement and defect prediction tool: Dione. Our tool enables organizations to measure, monitor, and control product quality through learning based defect prediction. Similar existing tools either provide data collection and analytics, or work just as a prediction engine. Therefore, companies need to deal with multiple tools with incompatible interfaces in order to deploy a complete measurement and prediction solution. Dione provides a fully integrated solution where data extraction, defect prediction and reporting steps fit seamlessly. In this paper, we present the major functionality and architectural elements of Dione followed by an overview of our demonstration.