On Asynchronous Session Semantics

This paper studies a behavioural theory of the π-calculus with session types under the fundamental principles of the practice of distributed computing — asynchronous communication which is order-preserving inside each connection (session), augmented with asynchronous inspection of events (message arrivals). A new theory of bisimulations is introduced, distinct from either standard asynchronous or synchronous bisimilarity, accurately capturing the semantic nature of session-based asynchronously communicating processes augmented with event primitives. The bisimilarity coincides with the reduction-closed barbed congruence. We examine its properties and compare them with existing semantics. Using the behavioural theory, we verify that the program transformation of multithreaded into event-driven session based processes, using Lauer-Needham duality, is type and semantic preserving

Uncertainty-aware estimation of population abundance using machine learning

Machine Learning is widely used for mining collections, such as images, sounds, or texts, by classifying their elements into categories. Automatic classification based on supervised learning requires groundtruth datasets for modeling the elements to classify, and for testing the quality of the classification. Because collecting groundtruth is tedious, a method for estimating the potential errors in large datasets based on limited groundtruth is needed. We propose a method that improves classification quality by using limited groundtruth data to extrapolate the po-tential errors in larger datasets. It significantly improves the counting of elements per class. We further propose visualization designs for understanding and evaluating the classification un-certainty. They support end-users in considering the impact of potential misclassifications for interpreting the classification output. This work was developed to address the needs of ecologists studying fish population abundance using computer vision, but generalizes to a larger range of applications. Our method is largely applicable for a variety of Machine Learning technologies, and our visualizations further support their transfer to end-users

Formal approaches to information-hiding (Tutorial)

In this survey paper we consider the class of protocols for information-hiding which use randomization to obfuscate the link between the observables and the information to be protected. We focus on the problem of formalizing the notion of information hiding, and verifying that a given protocol achieves the intended degree of protection. Without the pretense of being omni-comprehensive, we review the main approaches that have been explored in literature: possibilistic, probabilistic, information-theoretic, and statistical

Concurrency Can't Be Observed, Asynchronously

International audienceThe paper is devoted to an analysis of the concurrent features of asynchronous systems. A preliminary step is represented by the introduction of a non-interleaving extension of barbed equivalence. This notion is then exploited in order to prove that concurrency cannot be observed through asynchronous interactions, i.e., that the interleaving and concurrent versions of a suitable asynchronous weak equivalence actually coincide. The theory is validated on two case studies, related to nominal calculi (π-calculus) and visual specification formalisms (Petri nets)