Session Types with Runtime Adaptation: Overview and Examples

In recent work, we have developed a session types discipline for a calculus that features the usual constructs for session establishment and communication, but also two novel constructs that enable communicating processes to be stopped, duplicated, or discarded at runtime. The aim is to understand whether known techniques for the static analysis of structured communications scale up to the challenging context of context-aware, adaptable distributed systems, in which disciplined interaction and runtime adaptation are intertwined concerns. In this short note, we summarize the main features of our session-typed framework with runtime adaptation, and recall its basic correctness properties. We illustrate our framework by means of examples. In particular, we present a session representation of supervision trees, a mechanism for enforcing fault-tolerant applications in the Erlang language.Comment: In Proceedings PLACES 2013, arXiv:1312.221

Auto-Mobiles: Optimised Message-Passing

Some message-passing concurrent systems, such as occam 2, prohibit aliasing of data objects. Communicated data must thus be copied, which can be time-intensive for large data packets such as video frames. We introduce automatic mobility, a compiler optimisation that performs communications by reference and deduces when these communications can be performed without copying. We discuss bounds for speed-up and memory use, and benchmark the automatic mobility optimisation. We show that in the best case it can transform an operation from being linear with respect to packet size into constant-time

An automaton over data words that captures EMSO logic

We develop a general framework for the specification and implementation of systems whose executions are words, or partial orders, over an infinite alphabet. As a model of an implementation, we introduce class register automata, a one-way automata model over words with multiple data values. Our model combines register automata and class memory automata. It has natural interpretations. In particular, it captures communicating automata with an unbounded number of processes, whose semantics can be described as a set of (dynamic) message sequence charts. On the specification side, we provide a local existential monadic second-order logic that does not impose any restriction on the number of variables. We study the realizability problem and show that every formula from that logic can be effectively, and in elementary time, translated into an equivalent class register automaton

Lambda Calculus in Core Aldwych

Core Aldwych is a simple model for concurrent computation, involving the concept of agents which communicate through shared variables. Each variable will have exactly one agent that can write to it, and its value can never be changed once written, but a value can contain further variables which are written to later. A key aspect is that the reader of a value may become the writer of variables in it. In this paper we show how this model can be used to encode lambda calculus. Individual function applications can be explicitly encoded as lazy or not, as required. We then show how this encoding can be extended to cover functions which manipulate mutable variables, but with the underlying Core Aldwych implementation still using only immutable variables. The ordering of function applications then becomes an issue, with Core Aldwych able to model either the enforcement of an ordering or the retention of indeterminate ordering, which allows parallel execution

Teacher Evaluations in the Special Education Setting: Voices from the Field

National policy mandates have placed greater accountability on districts and schools to improve the outcomes of every student, including students with disabilities. Teacher evaluation systems that accurately identify effective teachers and their impact on student learning have resulted in the widespread design and implementation of new teacher evaluation systems. Nevertheless, limited exploration related to the evaluation of special education teachers exists. Using a qualitative, multi-case study research design, we sought to gain insight into the perceptions and experiences of special education teachers and administrators to better understand (a) the relationship between teacher evaluation and teacher effectiveness; (b) the ways in which educators approach the challenges of applying teacher evaluation systems for special education teachers; and (c) the ways in which teacher evaluation processes support the professional growth and development of special education teachers. The challenges involved in evaluating special education teachers with a uniform teacher evaluation protocol instrument are presented. The need to be able to accurately appraise special education teachers within an inclusive classroom setting, apply criteria from the observation protocol to special education students, and lack of appraisers� knowledge of the roles and expertise of special education teachers were identified. Recommendations for improvement are provided.Educatio

Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking

This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications