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FLEX-RCA: a lean-based method for root cause analysis in software process improvement
Volvo Cars, SWE.
Chalmers, swe.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik. Blekinge Inst Technol, Software Engn, SE-37179 Karlskrona, Sweden..
Volvo Cars, SWE.
2019 (Engelska)Ingår i: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, Vol. 27, nr 1, s. 389-428Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
SPRINGER , 2019. Vol. 27, nr 1, s. 389-428
Nyckelord [en]
Organizational management and coordination, Communication, Software engineering, Software-intensive systems, Automotive industry, Case study, Lean product development, Agile, Process improvement
Nationell ämneskategori
Programvaruteknik
Identifikatorer
URN: urn:nbn:se:bth-17827DOI: 10.1007/s11219-018-9408-8ISI: 000462236000011OAI: oai:DiVA.org:bth-17827DiVA, id: diva2:1305692
Tillgänglig från: 2019-04-18 Skapad: 2019-04-18 Senast uppdaterad: 2019-04-24Bibliografiskt granskad

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