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FLEX-RCA: a lean-based method for root cause analysis in software process improvement
Volvo Cars, SWE.
Chalmers, swe.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering. Blekinge Inst Technol, Software Engn, SE-37179 Karlskrona, Sweden..
Volvo Cars, SWE.
2019 (English)In: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, Vol. 27, no 1, p. 389-428Article in journal (Refereed) Published
Abstract [en]

Software process improvement (SPI) is an instrument to increase the productivity of, and the quality of work, in software organizations. However, a majority of SPI frameworks are too extensive or provide guidance and potential improvement areas at a high level, indicating only the symptoms, not the causes. Motivated by the industrial need of two Swedish automotive companies to systematically uncover the underlying root causes of high-level improvement issues identified in an SPI project-assessing inter-departmental interactions in large-scale software systems development-this paper advances a root cause analysis (RCA) method building on Lean Six Sigma, called Flex-RCA. Flex-RCA is used to delve deeper into challenges identified to find root causes as a part of the evaluation and subsequent improvement activities. We also demonstrate and evaluate Flex-RCA's industrial applicability in a case study. An overall conclusion is that the use of Flex-RCA was successful, showing that it had the desired effect of both producing a broad base of causes on a high level and, more importantly, enabling an exploration of the underlying root causes.

Place, publisher, year, edition, pages
SPRINGER , 2019. Vol. 27, no 1, p. 389-428
Keywords [en]
Organizational management and coordination, Communication, Software engineering, Software-intensive systems, Automotive industry, Case study, Lean product development, Agile, Process improvement
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17827DOI: 10.1007/s11219-018-9408-8ISI: 000462236000011OAI: oai:DiVA.org:bth-17827DiVA, id: diva2:1305692
Available from: 2019-04-18 Created: 2019-04-18 Last updated: 2019-04-24Bibliographically approved

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Gorschek, Tony

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  • de-DE
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