Quantitative Evaluation of Software Quality Metrics in Open-Source Projects

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 in...

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Main Author: Barkmann, Henrike
Format: Others
Language:English
Published: Växjö universitet, Matematiska och systemtekniska institutionen 2009
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2562
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spelling ndltd-UPSALLA1-oai-DiVA.org-vxu-25622018-01-14T05:13:26ZQuantitative Evaluation of Software Quality Metrics in Open-Source ProjectsengBarkmann, HenrikeVäxjö universitet, Matematiska och systemtekniska institutionen2009software quality metricsdistributionsComputer SciencesDatavetenskap (datalogi)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 objectoriented metrics suites. Besides, we present early results of typical metrics values and possible thresholds. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2562Rapporter från MSI, 1650-2647 ; 1650-2647application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic software quality metrics
distributions
Computer Sciences
Datavetenskap (datalogi)
spellingShingle software quality metrics
distributions
Computer Sciences
Datavetenskap (datalogi)
Barkmann, Henrike
Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
description 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 objectoriented metrics suites. Besides, we present early results of typical metrics values and possible thresholds.
author Barkmann, Henrike
author_facet Barkmann, Henrike
author_sort Barkmann, Henrike
title Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
title_short Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
title_full Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
title_fullStr Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
title_full_unstemmed Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
title_sort quantitative evaluation of software quality metrics in open-source projects
publisher Växjö universitet, Matematiska och systemtekniska institutionen
publishDate 2009
url http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2562
work_keys_str_mv AT barkmannhenrike quantitativeevaluationofsoftwarequalitymetricsinopensourceprojects
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