K-Taint: an executable rewriting logic semantics for taint analysis in the K framework

The K framework is a rewrite logic-based framework for defining programming language semantics suitable for formal reasoning about programs and programming languages. In this paper, we present K-Taint, a rewriting logic-based executable semantics in the K framework for taint analysis of an imperative programming language. Our K semantics can be seen as a sound approximation of programs semantics in the corresponding security type domain. More specifically, as a foundation to this objective, we extend to the case of taint analysis the semantically sound flow-sensitive security type system by Hunt and Sands's, considering a support to the interprocedural analysis as well. With respect to the existing methods, K-Taint supports context- and flow-sensitive analysis, reduces false alarms, and provides a scalable solution. Experimental evaluation on several benchmark codes demonstrates encouraging results as an improvement in the precision of the analysis.This work is partially supported by the research grant (SB/FTP/ETA-315/2013) from the Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India

Severe acute respiratory syndrome coronavirus 2 Omicron variant and psychological distress among frontline nurses in a major COVID-19 center: Implications for supporting psychological well-being

Background: Coronavirus outbreak severely affected the psychological health of frontline health-care workers, including nurses. Nurses relatively face many more psychological problems compared to other health-care workers. This study aimed to assess nurses' fear, stress, and anxiety status during the Omicron, a new variant of the severe acute respiratory syndrome coronavirus 2, outbreak in India. Materials and Methods: This questionnaire survey included 350 frontline nurses working at a tertiary care teaching hospital in North India. The information was collected using the Coronavirus Anxiety Scale, Impact of Event Scale-Revised, and Fear of COVID-19 Scale. Nurses working in the hospital since COVID-19 outbreak were included in the study. Appropriate descriptive and inferential statistics were applied to compute the results. Results: Nurses hospitalized after contracting an infection (odds ratio [OR] – 3.492, 95% confidence interval – 1.644–9.442, P < 0.002) and attended training on COVID-19 (OR – 2.644, 95% CI – 1.191–5.870, P < 0.017) reported high distress than their counterparts. Likewise, nurses hospitalized after contracting an infection (β = 3.862, P < 0.001 vs. β = 2.179, P < 0.001) and have no training exposure on COVID-19 management and care (β = 2.536, P = 0.001 vs. β = 0.670, P = 0.039) reported higher fear and anxiety, respectively. Likewise, married participants (β = 1.438, P < 0.036) who lost their friends and colleagues in the pandemic (β = 0.986, P = 0.020) reported being more frightened and anxious. Conclusions: Participants reported experiencing psychological burdens, especially nurses hospitalized after contracting an infection and who lost their friends and colleagues to COVID-19. High psychological distress may be a potential indicator of future psychiatric morbidity. Authors recommend a variant-specific training to improve nurses' mental health to combat the pandemic