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Prevalence of continuous integration failures in industrial systems with hardware-in-the-loop testing
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS. Ericsson AB, Stockholm, Sweden..
Ericsson AB, Stockholm, Sweden.;Mälardalen Univ, Västerås, Sweden..
Ericsson AB, Stockholm, Sweden..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS. Ericsson AB, Stockholm, Sweden..
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2022 (English)In: 2022 IEEE INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING WORKSHOPS (ISSREW 2022), Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 61-66Conference paper, Published paper (Refereed)
Abstract [en]

Faults in the automated continuous integration (CI) process can seriously impact the development of industrial code. To reduce manual intervention in automated CI processes, we want to understand better the CI systems' failure distribution to improve efficiency, reliability, and maintainability. This paper investigates failures in CI in four large industrial projects. We gather 11 731 builds over six months, identifying 1 414 failing builds. We also identify the distribution of different types of build failures in each of the four CI projects. Our results show that compilation is the most significant individual cause of failure with 47 %, followed by testing at 36 %. The checkout step with associated checks also incurs a non-negligible portion of failures with 12 %. Furthermore, we identify 14 distinct types of failures in the testing step. We conclude that configuration problems are a significant issue, as pipeline scripting and dependency errors make up a large number of failures.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. p. 61-66
Series
IEEE International Symposium on Software Reliability Engineering Workshops, ISSN 2375-821X
Keywords [en]
continuous integration, failure classification, industry study, embedded system
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:kth:diva-324523DOI: 10.1109/ISSREW55968.2022.00040ISI: 000909333700011Scopus ID: 2-s2.0-85146335651OAI: oai:DiVA.org:kth-324523DiVA, id: diva2:1741753
Conference
33rd IEEE International Symposium on Software Reliability Engineering (ISSRE), OCT 31-NOV 03, 2022, Charlotte, NC
Note

QC 20230307

Available from: 2023-03-07 Created: 2023-03-07 Last updated: 2023-03-07Bibliographically approved

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Fu, HanErmedahl, AndreasArtho, Cyrille

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  • apa
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