It is worth understanding state machines better because various kinds of systems can be formalized as state machines and therefore understanding state machines has something to do with comprehension of systems. Understanding state machines can be interpreted as knowing properties they enjoy and comprehension of systems is interpreted as knowing whether they satisfy requirements. We (mainly the second author) have developed a tool called SMGA that basically takes a finite sequence of states from a state machine and generates a graphical animation of the finite sequence or the state machine. Observing such a graphical animation helps us guess properties of the state machine. We should confirm whether the state machine enjoys the guessed properties because such guessed properties may not be true properties of the state machine. Model checking is one possible technique to do so. If the state machine has a fixed small number of reachable states, model checking is enough. Otherwise, however, it is not. If that is the case, we should use some other techniques to make sure that the system enjoys the guessed properties. Interactive theorem proving is one such technique. The paper reports on a case study in which a mutual exclusion protocol called Qlock is used as an example to exemplify the abovementioned idea or methodology.

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To evaluate a decentralised testing model and simplified treatment protocol of hepatitis C virus (HCV) infection to facilitate treatment scale-up in Myanmar, this prospective, observational study recruited HIV–HCV co-infected outpatients receiving sofosbuvir/daclatasvir in Yangon, Myanmar. The study examined the outcomes and factors associated with a sustained virological response (SVR). A decentralised “hub-and-spoke” testing model was evaluated where fingerstick capillary specimens were transported by taxi and processed centrally. The performance of the Xpert HCV VL Fingerstick Assay in detecting HCV RNA was compared to the local standard of care ( plasma HCV RNA collected by venepuncture). Between January 2019 and February 2020, 162 HCV RNA-positive individuals were identified; 154/162 (95%) initiated treatment, and 128/154 (84%) returned for their SVR12 visit. A SVR was achieved in 119/154 (77%) participants in the intent-to-treat population and 119/128 (93%) participants in the modified-intent-to-treat population. Individuals receiving an antiretroviral therapy were more likely to achieve a SVR (with an odds ratio (OR) of 7.16, 95% CI 1.03–49.50), while those with cirrhosis were less likely (OR: 0.26, 95% CI 0.07–0.88). The sensitivity of the Xpert HCV VL Fingerstick Assay was 99.4% (95% CI 96.7–100.0), and the specificity was 99.2% (95% CI 95.9–99.9). A simplified treatment protocol using a hub-and-spoke testing model of fingerstick capillary specimens can achieve an SVR rate in LMIC comparable to well-resourced high-income settings.

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