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Dione: An Integrated Measurement and Defect Prediction Solution

Caglayan, Bora; Tosun Misirli, Ayse; Calikli, Gul; Aytac, Turgay; Bener, Ayse and Turhan, Burak (2012). Dione: An Integrated Measurement and Defect Prediction Solution. In: 20th International Symposium on the Foundations of Software Engineering (ACM SIGSOFT 2012 FSE-20), 11-16 Nov 2012, Cary, North Carolina, USA.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1145/2393596.2393619
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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.

Item Type: Conference or Workshop Item
Keywords: software tool; measurement; software defect prediction
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 45351
Depositing User: Gul Calikli
Date Deposited: 24 Feb 2016 11:46
Last Modified: 07 Dec 2018 23:06
URI: http://oro.open.ac.uk/id/eprint/45351
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