Dione: An integrated measurement and defect prediction solution

Bora Caglayan; Ayse Tosun Misirli; Gul Calikli; Ayse Bener; Turgay Aytac; Burak Turhan

doi:10.1145/2393596.2393619

Dione: An integrated measurement and defect prediction solution

Bora Caglayan, Ayse Tosun Misirli, Gul Calikli, Ayse Bener, Turgay Aytac, Burak Turhan

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

9 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE 2012
DOIs	https://doi.org/10.1145/2393596.2393619
Publication status	Published - 24 Dec 2012
Externally published	Yes
Event	20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, FSE 2012 - Cary, NC, United States of America Duration: 11 Nov 2012 → 16 Nov 2012

Conference

Conference	20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, FSE 2012
Country/Territory	United States of America
City	Cary, NC
Period	11/11/12 → 16/11/12

Keywords

measurement
software defect prediction
software tool

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10.1145/2393596.2393619

Cite this

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title = "Dione: An integrated measurement and defect prediction solution",

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.",

keywords = "measurement, software defect prediction, software tool",

author = "Bora Caglayan and Misirli, {Ayse Tosun} and Gul Calikli and Ayse Bener and Turgay Aytac and Burak Turhan",

year = "2012",

month = dec,

day = "24",

doi = "10.1145/2393596.2393619",

language = "English",

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booktitle = "Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE 2012",

note = "20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, FSE 2012 ; Conference date: 11-11-2012 Through 16-11-2012",

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Caglayan, B, Misirli, AT, Calikli, G, Bener, A, Aytac, T & Turhan, B 2012, Dione: An integrated measurement and defect prediction solution. in Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE 2012. 20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, FSE 2012, Cary, NC, United States of America, 11/11/12. https://doi.org/10.1145/2393596.2393619

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AU - Caglayan, Bora

AU - Misirli, Ayse Tosun

AU - Calikli, Gul

AU - Bener, Ayse

AU - Aytac, Turgay

AU - Turhan, Burak

PY - 2012/12/24

Y1 - 2012/12/24

N2 - 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.

AB - 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.

KW - measurement

KW - software defect prediction

KW - software tool

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M3 - Conference Paper

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BT - Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE 2012

Y2 - 11 November 2012 through 16 November 2012

ER -

Dione: An integrated measurement and defect prediction solution

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Keywords

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