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Safety-Critical Systems and Agile Development: A Mapping Study

Paper i proceeding
Författare Rashidah Kasauli
Eric Knauss
Benjamin Kanagwa
Agneta Nilsson
Gul Calikli
Publicerad i 44TH EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA 2018)
ISBN 978-1-5386-7383-6
ISSN 1089-6503
Publiceringsår 2018
Publicerad vid Institutionen för data- och informationsteknik (GU)
Språk en
Ämnesord Safety-critical systems, agile, continuous integration, continuous delivery, continuous deployment, systematic mapping study
Ämneskategorier Programvaruteknik

Sammanfattning

Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g., to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g., restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multi-disciplinary environments. Additionally, we see the need for future work in the area of model use, i.e., information extraction from models by non-expert modellers.

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