Atomic components

There has been much interest in components that combine the best of state-based and event-based approaches. The interface of a component can be thought of as its specification and substituting components with the same interface cannot be observed by any user of the components. Here we will define the semantics of atomic components where both states and event can be part of the interface. The resulting semantics is very similar to that of (event only) processes. But it has two main novelties: one, it does not need recursion or unique fixed points to model nontermination; and two, the behaviour of divergence is modelled by abstraction, i.e. the construction of the observational semantics

State- and event-based refinement

In this paper we give simple example abstract data types, with atomic operations, that are related by data refinement under a definition used widely in the literature, but these abstract data types are not related by singleton failure refinement. This contradicts results found in the literature. Further we show that a common way to change a model of atomic operations to one of value passing operations actually changes the underlying atomic operational semantics

Liberalising Event B without changing it

We transfer a process algebraic notion of refinement to the B method by using the well-known bridge between the relational semantics underlying the B machines and the labelled transition system semantics of processes. Thus we define delta refinement on Event B systems. We then apply this new refinement to a problem from the literature that previously could only be solved by retrenchment

Constructing programs or processes

We define interacting sequential programs, motivated originally by constructivist considerations. We use them to investigate notions of implementation and determinism. Process algebras do not define what can be implemented and what cannot. As we demonstrate it is problematic to do so on the set of all processes. Guided by constructivist notions we have constructed interacting sequential programs which we claim can be readily implemented and are a subset of processes

LSB - Live and Safe B: Alternative semantics for Event B

We define two lifted, total relation semantics for Event B machines: Safe B for safety-only properties and Live B for liveness properties. The usual Event B proof obligations, Safe, are sufficient to establish Safe B refinement. Satisfying Safe plus a simple additional proof obligation ACT REF is sufficient to establish Live B refinement. The use of lifted, total relations both prevents the ambiguity of the unlifted relational semantics and prevents operations being clairvoyant

State-based and process-based value passing

State-based and process-based formalisms each come with their own distinct set of assumptions and properties. To combine them in a useful way it is important to be sure of these assumptions in order that the formalisms are combined in ways which have, or which allow, the intended combined properties. Consequently we cannot necessarily expect to take on state-based formalism and one process-based formalism and combine them and get something sensible, especially since the act of combining can have subtle consequences. Here we concentrate on value-passing, how it is treated in each formalism, and how the formalisms can be combined so as to preserve certain properties. Specifically, the aim is to take from the many process-based formalisms definitions that will best fit with our chosen stat-based formalism, namely Z, so that the fit is simple, has no unintended consequences and is as elegant as possible

Flexible refinement

To help make refinement more usable in practice we introduce a general, flexible model of refinement. This is defined in terms of what contexts an entity can appear in, and what observations can be made of it in those contexts. Our general model is expressed in terms of an operational semantics, and by exploiting the well-known isomorphism between state-based relational semantics and event-based labelled transition semantics we were able to take particular models from both the state- and event-based literature, reflect on them and gradually evolve our general model. We are also able to view our general model both as a testing semantics and as a logical theory with refinement as implication. Our general model can used as a bridge between different particular special models and using this bridge we compare the definition of determinism found in different special models. We do this because the reduction of nondeterminism underpins many definitions of refinement found in a variety of special models. To our surprise we find that the definition of determinism commonly used in the process algebra literature to be at odds with determinism as defined in other special models. In order to rectify this situation we return to the intuitions expressed by Milner in CCS and by formalising these intuitions we are able to define determinism in process algebra in such a way that it no longer at odds with the definitions we have taken from other special models. Using our abstract definition of determinism we are able to construct a new model, interactive branching programs, that is an implementable subset of process algebra. Later in the chapter we show explicitly how five special models, taken from the literature, are instances of our general model. This is done simply by fixing the sets of contexts and observations involved. Next we define vertical refinement on our general model. Vertical refinement can be seen both as a generalisation of what, in the literature, has been called action refinement or non-atomic refinement. Alternatively, by viewing a layer as a logical theory, vertical refinement is a theory morphism, formalised as a Galois connection. By constructing a vertical refinement between broadcast processes and interactive branching programs we can see how interactive branching programs can be implemented on a platform providing broadcast communication. But we have been unable to extend this theory morphism to implement all of process algebra using broadcast communication. Upon investigation we show the problem arises with the examples that caused the problem with the definition of determinism on process algebra. Finally we illustrate the usefulness of our flexible general model by formally developing a single entity that contains events that use handshake communication and events that use broadcast communication

Feature refinement

Development by formal stepwise refinement offers a guarantee that an implementation satisfies a specification. But refinement is frequently defined in such a restrictive way as to disallow some useful development steps. Here we de- fine feature refinement to overcome some limitations of re- finement and show its usefulness by applying it to examples taken from the literature. Using partial relations as a canonical state-based semantics and labelled transition systems as a canonical event-based semantics, we degine functions formally linking the state- and event-based operational semantics. We can then use this link to move notions of refinement between the event- and state-based worlds. An advantage of this abstract approach is that it is not restricted to a specific syntax or even a specific interpretation of the operational semantic

Refinement for Probabilistic Systems with Nondeterminism

Before we combine actions and probabilities two very obvious questions should be asked. Firstly, what does "the probability of an action" mean? Secondly, how does probability interact with nondeterminism? Neither question has a single universally agreed upon answer but by considering these questions at the outset we build a novel and hopefully intuitive probabilistic event-based formalism. In previous work we have characterised refinement via the notion of testing. Basically, if one system passes all the tests that another system passes (and maybe more) we say the first system is a refinement of the second. This is, in our view, an important way of characterising refinement, via the question "what sort of refinement should I be using?" We use testing in this paper as the basis for our refinement. We develop tests for probabilistic systems by analogy with the tests developed for non-probabilistic systems. We make sure that our probabilistic tests, when performed on non-probabilistic automata, give us refinement relations which agree with for those non-probabilistic automata. We formalise this property as a vertical refinement.Comment: In Proceedings Refine 2011, arXiv:1106.348