SOG-Based Multi-Core LTL Model Checking

International audienc

Hybrid Parallel Model Checking of Hybrid LTL on Hybrid State Space Representation

International audienc

Symbolic Observation Graph-Based Generation of Test Paths

International audienceThe paper introduces a theoretical foundation for generating abstract test paths related to Petri net specifications. Based on the structure of the Petri net model of the system, we first define the notion of unobservable transition. Unless such a transition is unreachable, we prove that its firing is necessarily ensured by the firing of another transition (namely observable transition) of the Petri net. We show that the set of observable transitions is the smallest set that guarantees the coverage of all the transitions of the Petri net model, i.e., any set of firing sequences of the model, namely observable traces, involving all the observable transitions passes eventually through the unobservable transitions as well. If some unobservable transitions are mandatory to trigger the execution of a test sub-sequence, observable traces are completed with such transitions to enhance the controllability of the test scenario. In addition to structurally identifying observable (and unobservable) transitions, we mainly propose two algorithms: the first allows to generate a set of observable paths ensuring full coverage of all the system transitions. It is based on an on-the-fly construction of a hybrid graph called the symbolic observation graph. The second algorithm completes the observable paths in order to explicitly cover the whole set of system’s transitions. The approach is implemented within an available prototype, and the preliminary experiments are promisin

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population