<div class="csl-bib-body">
<div class="csl-entry">Rausch, T. (2016). <i>Build failure prediction in continuous integration workflows</i> [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2016.37419</div>
</div>
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dc.identifier.uri
https://doi.org/10.34726/hss.2016.37419
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/3329
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dc.description
Zusammenfassung in deutscher Sprache
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dc.description.abstract
Continuous integration (CI) is a practice where developers integrate their work into the main stream of development frequently. A CI server monitors the source code repository of a project and automatically executes the software build process when new changes are checked in. If a build fails, developers have to identify and fix the cause of the broken build, leading to a delay in the integration process and stalling further development. Large software projects often have long running builds that exacerbate this problem. Despite the widespread use of CI, little is known about the multiplicity of errors that cause builds to fail. Yet, understanding when and why build errors occur is an important step towards improving developer productivity in the CI workflow. By identifying characteristics of development practices that cause build failures, we can predict preliminary results for an integration. This helps developers react to possible problems even before a build is initiated, thereby saving time and resources. In this thesis, we introduce CInsight, a framework for analyzing CI workflows and build failures. We conduct an empirical study on real-world data from 14 open source software projects. Data from source code repositories and build systems are explored to gather qualitative and quantitative evidence about the multiplicity and frequency of CI build errors. Statistical methods are used to examine the relationship between development practices and build failures. Based on the results, we devise a method for CI build failure prediction. Our results show that failing unit-tests and violations of code quality rules are the main causes for build failures. The statistical analyses reveal that the type and amount of previous errors are the strongest predictor for future failures. Our best prediction models yield average recall and precision values of 0.82 and 0.80, respectively. Furthermore, our approach allows to update a prediction during the execution of a build.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
Empirical Software Engineering
de
dc.subject
Machine Learning
de
dc.subject
Predictive Analytics
de
dc.subject
Continuous Integration
de
dc.subject
Build Failure Prediction
de
dc.subject
Empirical Software Engineering
en
dc.subject
Machine Learning
en
dc.subject
Predictive Analytics
en
dc.subject
Continuous Integration
en
dc.subject
Build Failure Prediction
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dc.title
Build failure prediction in continuous integration workflows
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dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.identifier.doi
10.34726/hss.2016.37419
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dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Thomas Rausch
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dc.publisher.place
Wien
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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tuw.publication.orgunit
E184 - Institut für Informationssysteme
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dc.type.qualificationlevel
Diploma
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dc.identifier.libraryid
AC13351644
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dc.description.numberOfPages
128
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dc.identifier.urn
urn:nbn:at:at-ubtuw:1-7311
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dc.thesistype
Diplomarbeit
de
dc.thesistype
Diploma Thesis
en
tuw.author.orcid
0000-0001-5988-9041
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dc.rights.identifier
In Copyright
en
dc.rights.identifier
Urheberrechtsschutz
de
tuw.advisor.staffStatus
staff
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tuw.advisor.orcid
0000-0001-6828-9945
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item.languageiso639-1
en
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item.openairetype
master thesis
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item.grantfulltext
open
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item.fulltext
with Fulltext
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item.cerifentitytype
Publications
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item.mimetype
application/pdf
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item.openairecristype
http://purl.org/coar/resource_type/c_bdcc
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item.openaccessfulltext
Open Access
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crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
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crisitem.author.orcid
0000-0001-5988-9041
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering