Predicting software build failure using source code metrics

aut.relation.endpage188
aut.relation.issue5
aut.relation.startpage177
aut.relation.volume1
aut.researcherConnor, Andrew Miles
dc.contributor.authorConnor, AM
dc.contributor.authorFinlay, J
dc.date.accessioned2014-04-11T09:53:54Z
dc.date.available2014-04-11T09:53:54Z
dc.date.copyright2011-09-15
dc.date.issued2011-09-15
dc.description.abstractIn this paper, we describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success or failure of an attempt to construct a working instance of the software product. We present results from a study using the J48 classification method used in conjunction with a number of attribute selection strategies applied to a set of source code metrics calculated from the code base at the beginning of a build cycle. The results indicate that only a relatively small number of the available software metrics that we considered have any significance for predicting the outcome of a build. These significant metrics are discussed and implication of the results discussed, particularly the relative difficulty of being able to predict failed build attempts. The results also indicate that there is some scope for predicting the outcomes of an attempt to construct a working instance of the software product by analysing the characteristics of the source code to be changed. This provides the opportunity for software project managers to estimate the risk exposure of the planned changes in the build prior to commencing the coding activities.
dc.identifier.citationInternational Journal of Information and Communication Technology Research, vol.1(5), pp.177 - 188
dc.identifier.issn2223-4985
dc.identifier.urihttps://hdl.handle.net/10292/7088
dc.publisherARPN International Journal of Information and Communication Technology Research
dc.relation.urihttp://esjournals.org//journaloftechnology/Download_September_pdf_1.php
dc.rightsInternational Journal of Information and Communication Technology Research is partly sponsored by some non-governmental organizations. Being part of open-access initiative, the published research papers are freely available to everyone and we don’t apply any subscription charges for our readers or libraries.
dc.rights.accessrightsOpenAccess
dc.subjectData mining
dc.subjectJazz
dc.subjectSoftware metrics
dc.subjectSoftware repositories
dc.titlePredicting software build failure using source code metrics
dc.typeJournal Article
pubs.elements-id45424
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Interdisplinary Unit
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