Benefits of Session Types for software Development

Session types are a formalism used to specify and check the correctness of communication based systems. Within their scope, they can guarantee the absence of communication errors such as deadlock, sending an unexpected message or failing to handle an incoming message. Introduced over two decades ago, they have developed into a significant theme in programming languages. In this paper we examine the beliefs that drive research into this area and make it popular. We look at the claims and motivation behind session types throughout the literature. We identify the hypotheses upon which session types have been designed and implemented, and attempt to clarify and formulate them in a more suitable manner for testing

Visualizing the Results of a Complex Hybrid Dynamic-Static Analysis

Complex static or hybrid static-dynamic analyses produce large quantities of structured data. In the past, this data was generally intended for use by compilers or other software tools that used the produced information to transform the application being analyzed. However, it is becomingly increasingly common for the results of these analyses to be used directly by humans. For example, in our own prior work we have developed a hybrid dynamic-static escape analysis intended to help developers identify sources of object churn within large framework-base applications. In order to facilitate human use of complex analysis results, visualizations need to be developed that allow a user to browse these results and to identify the points of interest within these large data sets. In this paper we present Hi-C, a visualization tool for our hybrid escape analysis that has been implemented as an Eclipse plugin. We show how Hi-C can help developers identify sources of object churn in a large framework-based application and how we have used the tool to assist in understanding the results of a complex analysis

Developing front-end Web 2.0 technologies to access services, content and things in the future Internet

The future Internet is expected to be composed of a mesh of interoperable web services accessible from all over the web. This approach has not yet caught on since global user?service interaction is still an open issue. This paper states one vision with regard to next-generation front-end Web 2.0 technology that will enable integrated access to services, contents and things in the future Internet. In this paper, we illustrate how front-ends that wrap traditional services and resources can be tailored to the needs of end users, converting end users into prosumers (creators and consumers of service-based applications). To do this, we propose an architecture that end users without programming skills can use to create front-ends, consult catalogues of resources tailored to their needs, easily integrate and coordinate front-ends and create composite applications to orchestrate services in their back-end. The paper includes a case study illustrating that current user-centred web development tools are at a very early stage of evolution. We provide statistical data on how the proposed architecture improves these tools. This paper is based on research conducted by the Service Front End (SFE) Open Alliance initiative

Economic Crisis, Innovation Strategies and Firm Performance. Evidence from Italian Firm-level Data

Several empirical works have shown the robust and positive relation between growth and innovation at macroeconomic level and between firm economic performance and innovation at microeconomic level. However, the economists have had less opportunities to study such linkages during severe global downturns of the economic cycle. Moreover, the present disruptive economic downturn has forced the firms to implement survival strategies. One of such strategic behaviour regards the way of intervention on product and process areas through innovative actions. Focusing the attention on the micro level, the present work provides an empirical analysis on the basis of more than 500 Italian manufacturing firms located in Emilia-Romagna region, with the aim of disentangling the relations between pre-crisis innovation strategies and firm economic performance during the crisis as well as the linkages between the innovative actions taken to react to the recession's challenges and the economic performance in the recession. The results suggest the existence of strong relationships between past innovative activities and the capacity to react to the challenges brought by the crisis through innovative actions along product, process and organization/HRM dimensions, although the role of complementarities among past innovative activities does not emerge robustly. When the dependent variables are performance indicators the impact of pre-crisis innovation strategies emerges as robust for technological and organizational spheres, while intense innovative activities before the crisis on spheres like ICT, training and environment are detrimental for performances in the crisis. It seems that when the crisis hits those firms in a process of quite radical transformation and change, then the negative economic consequences of the recession are worse than in the case of firms on a more stable, less dynamic path.innovation strategies; economic crisis; firm performance

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

From Word to Sense Embeddings: A Survey on Vector Representations of Meaning

Over the past years, distributed semantic representations have proved to be effective and flexible keepers of prior knowledge to be integrated into downstream applications. This survey focuses on the representation of meaning. We start from the theoretical background behind word vector space models and highlight one of their major limitations: the meaning conflation deficiency, which arises from representing a word with all its possible meanings as a single vector. Then, we explain how this deficiency can be addressed through a transition from the word level to the more fine-grained level of word senses (in its broader acceptation) as a method for modelling unambiguous lexical meaning. We present a comprehensive overview of the wide range of techniques in the two main branches of sense representation, i.e., unsupervised and knowledge-based. Finally, this survey covers the main evaluation procedures and applications for this type of representation, and provides an analysis of four of its important aspects: interpretability, sense granularity, adaptability to different domains and compositionality.Comment: 46 pages, 8 figures. Published in Journal of Artificial Intelligence Researc

Optical Properties of Correlated Materials -- or Why Intelligent Windows may look Dirty

Materials with strong electronic Coulomb correlations play an increasing role in modern materials applications. "Thermochromic" systems, which exhibit thermally induced changes in their optical response, provide a particularly interesting case. The optical switching associated with the metal-insulator transition of vanadium dioxide, for example, has been proposed for use in numerous applications, ranging from anti-laser shields to "intelligent" windows, which selectively filter radiative heat in hot weather conditions. Are present-day electronic structure techniques able to describe, or -- eventually even predict -- such a kind of behavior ? How far are we from materials design using correlated oxides ? These are the central questions we try to address in this article. We review recent attempts of calculating optical properties of correlated materials within dynamical mean field theory, and summarize results for vanadium dioxide obtained within a novel scheme aiming at particularly simple and efficient calculations of optical transition matrix elements within localized basis sets. Finally, by optimizing the geometry of "intelligent windows", we argue that this kind of technique can in principle be used to provide guidance for experiments, thus giving a rather optimistic answer to the above questions.Comment: 11 pages, 4 figures, Phys. Status Solidi B 246, in print (2009), also available as psi-k Scientific Highlight of the Month, no. 88, August 2008, http://www.psi-k.org/newsletters/News_88/Highlight_88.pd