Refining Nodes and Edges of State Machines

State machines are hierarchical automata that are widely used to structure complex behavioural specifications. We develop two notions of refinement of state machines, node refinement and edge refinement. We compare the two notions by means of examples and argue that, by adopting simple conventions, they can be combined into one method of refinement. In the combined method, node refinement can be used to develop architectural aspects of a model and edge refinement to develop algorithmic aspects. The two notions of refinement are grounded in previous work. Event-B is used as the foundation for our refinement theory and UML-B state machine refinement influences the style of node refinement. Hence we propose a method with direct proof of state machine refinement avoiding the detour via Event-B that is needed by UML-B

ПРОФИЛАКТИКА ТУБЕРКУЛЕЗА: СОВРЕМЕННЫЕ ПОДХОДЫ К РАЗРАБОТКЕ ПРОТИВОТУБЕРКУЛЕЗНЫХ ВАКЦИН

This review is focused on recent advances in development of new vaccines for the prevention of tuberculosis. The main reasons for lack of BCG vaccine efficacy in different populations and geographic regions are presented. Design of new vaccines based on live modified strains of Mycobacterium bovis BCG, attenuated strains of Mycobacterium tuberculosis, recombinant proteins and viral vectors is considered in the specific examples. The usage of the heterologous «prime-boost» vaccination strategy against tuberculosis is discussed. В обзоре освещены современные достижения в области разработки новых вакцин для профилактики туберкулеза. Представлены основные причины недостаточной эффективности вакцины БЦЖ в различных популяциях и географических регионах. На конкретных примерах рассмотрены направления дизайна новых вакцин на основе живых модифицированных штаммов Mycobacterium bovis БЦЖ, аттенуированных штаммов Mycobacterium tuberculosis, рекомбинантных белков и вирусных векторов. Обсуждается перспектива применения схемы гетерологичной «prime-boost» вакцинации против туберкулеза.

Constraint Methods for Modal Satisfiability

Modal and modal-like formalisms such as temporal or description logics go beyond propositional logic by introducing operators that allow for a guarded form of quantification over states or paths of transition systems. Thus, they are more expressive than propositional logic, yet computationally better behaved than first-order logic. We propose constraint-based methods to model and solve modal satisfiability problems. We model the satisfiability of basic modal formulas via appropriate sets of finite constraint satisfaction problems, and then resolve these via constraint solvers. The domains of the constraint satisfaction problems contain other values than just the Boolean 0 or 1; for these values, we create specialised constraints that help us steer the decision procedure and so keep the modal search tree as small as possible. We show experimentally that this constraint modelling gives us a better control over the decision procedure than existing SAT-based models