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Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi. (Software Technology Group)
Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi. (Software Technology Group)
Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Datalogi. (Software Technology Group)ORCID iD: 0000-0002-7565-3714
2009 (English)In: Proceedings of The 2009 IEEE International Workshop on Quantitative Evaluation of large-scale Systems and Technologies (QuEST09), IEEE Computer Society, 2009Conference paper, Published paper (Refereed)
Abstract [en]

The validation of software quality metrics lacks statistical significance. One reason for this is that the data collection requires quite some effort. To help solve this problem, we develop tools for metrics analysis of a large number of software projects (146 projects with ca. 70.000 classes and interfaces and over 11 million lines of code). Moreover, validation of software quality metrics should focus on relevant metrics, i.e., correlated metrics need not to be validated independently. Based on our statistical basis, we identify correlation between several metrics from well-known object-oriented metrics suites. Besides, we present early results of typical metrics values and possible thresholds.

Place, publisher, year, edition, pages
IEEE Computer Society, 2009.
Research subject
Computer and Information Sciences Computer Science
Identifiers
URN: urn:nbn:se:vxu:diva-3954OAI: oai:DiVA.org:vxu-3954DiVA, id: diva2:203911
Available from: 2009-01-07 Created: 2009-01-07 Last updated: 2017-04-19Bibliographically approved

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Lincke, RüdigerLöwe, Welf

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Barkmann, HenrikeLincke, RüdigerLöwe, Welf
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