This paper describes the participation of women in computing in more than 30 countries, by focussing on participation at undergraduate level. A brief discussion covers how societal and cultural factors may affect women's participation. Statistics from many different sources are presented for comparison. Generally, participation is low -most countries fall in the 10-40% range with a few below 10% and a few above 40%.

Hybrid systems are manifest in both the natural and the engineered world, and their complex nature, mixing discrete control and continuous evolution, make it difficult to predict their behaviour. In recent years several process algebras for modelling hybrid systems have appeared in the literature, aimed at addressing this problem. These all assume that continuous variables in the system are modelled monolithically, often with differential equations embedded explicitly in the syntax of the process algebra expression. In HYPE an alternative approach is taken which offers finer-grained modelling with each flow or influence affecting a variable modelled separately. The overall behaviour then emerges as the composition of flows. In this paper we give a detailed account of the HYPE process algebra, its semantics, and its use for verification of systems. We establish both syntactic conditions (well-definedness) and operational restrictions (well-behavedness) to ensure reasonable behaviour in HYPE models. Furthermore we consider how the equivalence relation defined for HYPE relates to other relations previously proposed in the literature, demonstrating that our fine-grained approach leads to a more discriminating notion of equivalence. We present the HYPE model of a standard hybrid system example, both establishing that our approach can reproduce the previously obtained results and demonstrating how our compositional approach supports variations of the problem in a straightforward and flexible way

In this paper we present CARMA, a language recently defined to support specification and analysis of collective adaptive systems. CARMA is a stochastic process algebra equipped with linguistic constructs specifically developed for modelling and programming systems that can operate in openended and unpredictable environments. This class of systems is typically composed of a huge number of interacting agents that dynamically adjust and combine their behaviour to achieve specific goals. A CARMA model, termed a collective, consists of a set of components, each of which exhibits a set of attributes. To model dynamic aggregations, which are sometimes referred to as ensembles, CARMA provides communication primitives that are based on predicates over the exhibited attributes. These predicates are used to select the participants in a communication. Two communication mechanisms are provided in the CARMA language: multicast-based and unicast-based. In this paper, we first introduce the basic principles of CARMA and then we show how our language can be used to support specification with a simple but illustrative example of a socio-technical collective adaptive system.

Students struggle to understand recursion and we need to find good ways to teach the concept. We believe that an understanding of the mental models of recursion that students develop will assist us in teaching them more effectively. In 2003 we reported on a study of the mental models our students developed. This paper discusses some changes that we made to our teaching in 2003 after that study. An analysis of the students' mental models in 2003, 2004 and 2005 shows that more students are developing the copies model of recursion which is always a viable model.

The process algebra HYPE was recently proposed as a fine-grained modelling approach for capturing the behaviour of hybrid systems. In the original proposal, each flow or influence affecting a variable is modelled separately and the overall behaviour of the system then emerges as the composition of these flows. The discrete behaviour of the system is captured by instantaneous actions which might be urgent, taking effect as soon as some activation condition is satisfied, or non-urgent meaning that they can tolerate some (unknown) delay before happening. In this paper we refine the notion of non-urgent actions, to make such actions governed by a probability distribution. As a consequence of this we now give HYPE a semantics in terms of Transition-Driven Stochastic Hybrid Automata, which are a subset of a general class of stochastic processes termed Piecewise Deterministic Markov Processes

Spatially distributed collective adaptive systems are an important class of systems, which pose significant challenges to modelling due to the size and complexity of their state spaces. This problem is acute when the dynamic behaviour of the system must be captured, for example in order to predict system performance. In this paper we present an abstraction technique which automatically derives a moment-closure approximation of the dynamic behaviour of a spatially distributed collective adaptive system from a discrete representation of the entities involved. The moment-closure technique is demonstrated to give accurate estimates of dynamic behaviour, although the number of ordinary differential equations generated for the second order joint moments can grow large in some cases. For these cases, we propose a rigorous model reduction technique and demonstrate its use to substantially reduce the computational effort with only limited impact on the accuracy if the reduction threshold is set appropriately. All the techniques reported in this paper are implemented in a tool which is freely available for download.

We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the network is modelled stochastically, and instantaneous decisions are modelled as discrete events. Our model describes a network of stationary video sensors with a mobile ferry which collects data from the sensors and delivers it to the base station. We consider different mobility models and different buffer sizes for the ferries. This case study illustrates the flexibility and expressive power of stochastic HYPE. We also discuss the software that enables us to describe stochastic HYPE models and simulate them

In order to circumvent the problem of state-space explosion of large-scale Markovian models, the stochastic process algebra PEPA has been given a fluid semantics based on ordinary differential equations, treating all entities as continuous. However, low numbers of instances and/or relatively slow dynamics may make such approximation too coarse for some parts of the system. To deal with such situations, we propose an hybrid semantics lying between these two extremes, treating parts of the system as discrete and stochastic and others as continuous and deterministic. The underlying mathematical object for the quantitative evaluation is a stochastic hybrid automaton. A case study of a client/server system with breakdowns and repairs is used to discuss the accuracy and the cost of this hybrid analysis