Program Transformation for Development, Verification, and Synthesis of Software

In this paper we briefly describe the use of the program transformation methodology for the development of correct and efficient programs. We will consider, in particular, the case of the transformation and the development of constraint logic programs

Re-reading Jevons's Principles of Science - Induction Redux

In this paper I try to substantiate the thesis that Jevons may have been too harsh on the vices of induction and generously optimistic about the virtues of deduction, as discussed, primarily, in his magnum opus, The Principles of Science [6]. With this aim in mind the paper attempts to suggest (modern), recursion theoretic, theoretical technologies that could reduce and, under conditions that I claim would be acceptable to Jevons, even eliminate the inductive indeterminacies that he had emphasised.Jevons, Inductiion, Inductive Inference, Bayes's Rule

The importance of information flows temporal attributes for the efficient scheduling of dynamic demand responsive transport services

The operation of a demand responsive transport service usually involves the management of dynamic requests. The underlying algorithms are mainly adaptations of procedures carefully designed to solve static versions of the problem, in which all the requests are known in advance. However there is no guarantee that the effectiveness of an algorithm stays unchanged when it is manipulated to work in a dynamic environment. On the other hand, the way the input is revealed to the algorithm has a decisive role on the schedule quality. We analyze three characteristics of the information flow (percentage of real-time requests, interval between call-in and requested pickup time and length of the computational cycle time), assessing their influence on the effectiveness of the scheduling proces

Coding and childhood between play and learning: Research on the impact of coding in the learning of 4-year-olds

We propose the results of a research that combines the educational and psychological media approach, to verify the pedagogical potential of coding and robotics in the learning processes of 4-year-old children at the cognitive and socio-relational level. The study investigated the impact of unplugged and plugged coding on the skills of spatiality, movement and prob- lem-solving skills, storage and decoding of progressively more complex indications, and single-group interaction of 51 children and three kindergartens using storytelling and the educational robot Cubetto. The work is based on the research carried out by Lee (2020) on the inclusion of coding in early childhood, the the- oretical references of Wing (2010) about computational thinking and the theoretical frameworks proposed by Bers (2020) regarding coding as a playful dimension. The data collected through the quantitative and qualitative tools of a pre- and post-intervention questionnaire to educators and a checklist of observations on children recorded the following: • an increase in children’s space, motor and information-storage/decoding skills; • a change in children’s collaborative skills when comparing the results of the plugged and unplugged coding workshops and • the impact of coding to increase children’s performance skills through narrative dimension and play

Computing Strong and Weak Permissions in Defeasible Logic

In this paper we propose an extension of Defeasible Logic to represent and compute three concepts of defeasible permission. In particular, we discuss different types of explicit permissive norms that work as exceptions to opposite obligations. Moreover, we show how strong permissions can be represented both with, and without introducing a new consequence relation for inferring conclusions from explicit permissive norms. Finally, we illustrate how a preference operator applicable to contrary-to-duty obligations can be combined with a new operator representing ordered sequences of strong permissions which derogate from prohibitions. The logical system is studied from a computational standpoint and is shown to have liner computational complexity

A Labelling Framework for Probabilistic Argumentation

The combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic argumentation is approached in the literature with different frameworks, pertaining to structured and abstract argumentation, and with respect to diverse types of uncertainty, in particular the uncertainty on the credibility of the premises, the uncertainty about which arguments to consider, and the uncertainty on the acceptance status of arguments or statements. Towards a general framework for probabilistic argumentation, we investigate a labelling-oriented framework encompassing a basic setting for rule-based argumentation and its (semi-) abstract account, along with diverse types of uncertainty. Our framework provides a systematic treatment of various kinds of uncertainty and of their relationships and allows us to back or question assertions from the literature

Teaching programming with computational and informational thinking

Computers are the dominant technology of the early 21st century: pretty well all aspects of economic, social and personal life are now unthinkable without them. In turn, computer hardware is controlled by software, that is, codes written in programming languages. Programming, the construction of software, is thus a fundamental activity, in which millions of people are engaged worldwide, and the teaching of programming is long established in international secondary and higher education. Yet, going on 70 years after the first computers were built, there is no well-established pedagogy for teaching programming. There has certainly been no shortage of approaches. However, these have often been driven by fashion, an enthusiastic amateurism or a wish to follow best industrial practice, which, while appropriate for mature professionals, is poorly suited to novice programmers. Much of the difficulty lies in the very close relationship between problem solving and programming. Once a problem is well characterised it is relatively straightforward to realise a solution in software. However, teaching problem solving is, if anything, less well understood than teaching programming. Problem solving seems to be a creative, holistic, dialectical, multi-dimensional, iterative process. While there are well established techniques for analysing problems, arbitrary problems cannot be solved by rote, by mechanically applying techniques in some prescribed linear order. Furthermore, historically, approaches to teaching programming have failed to account for this complexity in problem solving, focusing strongly on programming itself and, if at all, only partially and superficially exploring problem solving. Recently, an integrated approach to problem solving and programming called Computational Thinking (CT) (Wing, 2006) has gained considerable currency. CT has the enormous advantage over prior approaches of strongly emphasising problem solving and of making explicit core techniques. Nonetheless, there is still a tendency to view CT as prescriptive rather than creative, engendering scholastic arguments about the nature and status of CT techniques. Programming at heart is concerned with processing information but many accounts of CT emphasise processing over information rather than seeing then as intimately related. In this paper, while acknowledging and building on the strengths of CT, I argue that understanding the form and structure of information should be primary in any pedagogy of programming

Informatics Research Institute (IRIS) September 2008 newsletter

2007-8 was a very busy year for IRIS. It was a bumper year for visiting Profs with Prof Michael Myers visiting from New Zealand, Prof Brian Fitzgerald visiting from University of Limerick, Ireland, Prof. Uzay Kaymak visiting from Erasmus University Netherlands and Prof Steve Sawyer visiting from Pennsylvania State University, USA. Their visits enriched our doctoral school, seminar programme workshops and our research. We were very lucky to have such a distinguished line up of visiting professors and we offer them hearty thanks and hope to keep ongoing research links with them