Journal Article To Appear

Multiconcern Dependability-Centered Assurance via Qualitative and Quantitative Coanalysis

Authors Barbara Gallina Leonardo Montecchi André Luiz de Oliveira Lucas Bressan
Abstract
In various safety-critical domains, multi-concern claims, regarding multiple dependability attributes e.g., safety, security and their interplay, have become common and need to be justified based on evidence. At system design-level, evidence may include a combination of mono-concern as well as multi-concern analysis results. In this paper, to contribute to multi-concern assurance, we focus on system design, and we first present a high-level process that builds on top of the synergy between qualitative and quantitative dependability analysis techniques, which have been used for mono as well as multi-concern analysis. Then, we explain how to instantiate it within a specific domain, e.g., automotive. Finally, perspectives for future work are also sketched.
DOI 10.1109/MS.2022.3167370
Journal IEEE Software
Month April
Year 2022 (To appear)
Publisher IEEE
Citation
Bibtex
@article{2022SW,
  author = {Gallina, Barbara and Montecchi, Leonardo and de Oliveira, André Luiz and Bressan, Lucas},
  title = {{Multiconcern Dependability-Centered Assurance via Qualitative and Quantitative Coanalysis}},
  journal = {IEEE Software},
  publisher = {IEEE},
  pages = {-},
  month = {4},
  note = {\emph{To appear}},
  year = {2022}
}

Plain Text
B. Gallina, L. Montecchi, A. de Oliveira, L. Bressan. Multiconcern Dependability-Centered Assurance via Qualitative and Quantitative Coanalysis. In: IEEE Software, pp. - (April 2022).
 
 

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