Extending the theory of Owicki and Gries with asynchronous message passing

We describe an extension of the theory of Owicki and Gries (1976) to a programming language that supports asynchronous message passing based on unconditional send actions and conditional receive actions. The focus is on exploring the fitness of the extension for distributed program derivation. A number of experiments are reported, based on a running example problem, and with the aim of exploring design heuristics and of streamlining derivations and progress arguments.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

Bernstein's theory of pedagogic discourse: linguistics, educational policy and practice in the UK English/literacy classroom

In “The English Patient: English Grammar and teaching in the Twentieth Century”, Hudson and Walmsley (2005) contens that the decline of grammar in schools was linked to a similar decline in English universities, where no serious research or teaching on English grammar took place. This article argues that such a decline was due not only to a lack of research, but also because it suited educational policies of the time. It applies Bernstein’s theory of pedagogic discourse (1990 & 1996) to the case study of the debate surrounding the introduction of a national curriculum in English in England in the late 1980s and the National Literacy Strategy in the 1990s, to demonstrate the links between academic theory and educational policy.