Dione: An integrated measurement and defect prediction solution

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-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 languageEnglish
Title of host publicationProceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE 2012
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, FSE 2012 - Cary, NC, United States
Duration: 11 Nov 201216 Nov 2012

Publication series

NameProceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE 2012

Conference

Conference20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering, FSE 2012
Country/TerritoryUnited States
CityCary, NC
Period11/11/1216/11/12

Keywords

  • measurement
  • software defect prediction
  • software tool

Fingerprint

Dive into the research topics of 'Dione: An integrated measurement and defect prediction solution'. Together they form a unique fingerprint.

Cite this