Modeling the Variability of System Safety Analysis Using State-Machine Diagrams

Educational Software and Security Vulnerabilities: an experimental study

“…Safety standards provide requirements and guidance for analyzing and demonstrating safety properties at different levels. CRITVAR-ML (Bressan et al, 2021) (Bressan et al, 2022) is a modeling language, method, and tool to support the realization of domain variability into safety and security analysis artifacts and variability resolution into re-configurable MOF-compliant system models enriched with dependability information. It is a variability realization modeling language built upon the CVL standard to support engineers specifying mappings between domain problem-space features and finer-grained safety and security information stated as annotations (elements and property values) into MOF-compliant system models (e.g., SysML, AADL) in the solution space.…”

“…CRITIVAR (Bressan et al, 2021) (Bressan et al, 2022) main concepts will be used to evaluate the case study as well as the assessment model HEAVENS (Lautenbach, Almgren & Olovsson, 2021), described in the next section.…”

“…Our focus is the automatic detection of students with a great possibility of dropping out of school and students that need special attention in MOOC interactions. Actually, we are worried about the vulnerability of these plugins, considering threats to users' security (Bressan et al, 2021) (Bressan et al, 2022).…”

“…Besides our previous experience in safety and security analysis with CRITVAR-ML (Bressan et al, 2021) (Bressan et al, 2022), the evaluation methodology includes the assessment model HEAVENS (Lautenbach, Almgren & Olovsson, 2021), with minor calibrations of the parameters. The goal of threat analysis and risk assessment is to identify and rate potential threats in order to determine which ones need to be cybersecurity mitigated and what level of mitigation is required.…”