GABBRIELLI , Maurizio

Choreographic Programming is a paradigm for distributed programming, where high-level "Alice and Bob" descriptions of communications (choreographies) are used to synthesise correct-by-construction programs. However, implementations of choreographic models use message routing technologies distant from their related theoretical models (e.g.,...

In the context of Constraint Programming, a portfolio approach exploits the complementary strengths of a portfolio of different constraint solvers. The goal is to predict and run the best solver(s) of the portfolio for solving a new, unseen problem. In this work we reproduce, simulate, and evaluate the performance of different portfolio...

Application Programming Interfaces (APIs) are a standard feature of any application that exposes its functionalities to external invokers. APIs can becomposed thus obtaining new programs with new functionalities. However API composition easily becomes a frustrating and time-costly task that hinders API reuse. The issue derives from...

It is well recognized that a single, arbitrarily efficient solver can be significantly outperformed by a portfolio solver exploiting a combination of possibly slower on-average different solvers. Despite the success of portfolio solvers within the context of solving competitions, they are rarely used in practice. In this paper we give an...

The Constraint Programming (CP) paradigm allows to model and solve Constraint Satisfaction / Optimization Problems (CSPs / COPs). A CP Portfolio Solver is a particular constraint solver that takes advantage of a portfolio of different CP solvers in order to solve a given problem by properly exploiting Algorithm Selection techniques. In this...

In Constraint Programming (CP) a portfolio solver combines a variety of different constraint solvers for solving a given problem. This fairly recent approach enables to significantly boost the performance of single solvers, especially when multicore architectures are exploited. In this work we give a brief overview of the portfolio solver...

The Resource-Constrained Project Scheduling Problem (RCPSP) is a well-known scheduling problem aimed at minimizing the makespan of a project subject to temporal and resource constraints. Constraint Programming allows to model and solve RCPSPs in a natural and efficient way, especially when Lazy Clause Generation (LCG) techniques are employed....

In Constraint Programming (CP) a portfolio solver combines a variety of different constraint solvers for solving a given problem. This fairly recent approach enables to significantly boost the performance of single solvers, especially when multicore architectures are exploited. In this work we give a brief overview of the portfolio solver...

In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem. In this paper we introduce sunny-cp2: the first parallel CP portfolio solver that enables a dynamic , cooperative, and simultaneous execution of its solvers in a multicore setting. It...

Within the Constraint Satisfaction Problems (CSP) context, a methodology that has proven to be particularly performant consists of using a portfolio of different constraint solvers. Nevertheless, comparatively few studies and investigations have been done in the world of Constraint Optimization Problems (COP). In this work, we provide a...

In this paper, we propose to exploit the side-tuning framework for multimodal document classification. Side-tuning is a methodology for network adaptation recently introduced to solve some of the problems related to previous approaches. Thanks to this technique it is actually possible to overcome model rigidity and catastrophic forgetting of...

In this paper, we propose a method for assessing the risk of low achievement in primary and secondary school. We train three machine learning models with data collected by the Italian Ministry of Education through the INVALSI large-scale assessment tests. We compare the results of the trained models and evaluate the effectiveness of the...

The mere development of a software to predict University dropout is not sufficient for its effective implementation in the academic context. In order to exploit it as a tool supporting decision-making, such a software should be provided with information necessary for its integration into the decision-making processes of University governance....

Concurrent Constraint Programming (CCP) is a declarative model for concurrency where agents interact by telling and asking constraints (pieces of information) in a shared store. Some previous works have developed (approximated) declarative debuggers for CCP languages. However, the task of debugging concurrent programs remains difficult. In this...

This tutorial describes AIOCJ, which stands for Adaptive Interaction Oriented Choreographies in Jolie, a choreographic language for programming microservice-based applications which can be updated at runtime. The compilation of a single AIOCJ program generates the whole set of distributed microservices that compose the application. Adaptation...

The Internet of Things (IoT) promotes the communication among heterogeneous entities, from small sensors to Cloud systems. However, this is realized using a wide range of communication media and data protocols, usually incompatible with each other. Thus, IoT systems tend to grow as homogeneous isolated platforms, which hardly interact. To...

In Choreographic Programming, a choreography specifies in a single artefact the expected behaviour of all the participants in a distributed system. The choreography is used to synthesise correct-by-construction programs for each participant. In previous work, we defined Dynamic Choreographies to support the update of distributed systems at...

Concurrent Constraint Programming (CCP) is a declarative model for concurrency where agents interact by telling and asking constraints (pieces of information) in a shared store. Some previous works have developed (approximated) declarative debuggers for CCP languages. However, the task of debugging concurrent programs remains difficult. In this...

Humans are social animals and usually organize activities in groups. However, they are often willing to split temporarily a bigger group in subgroups to enhance their preferences. In this work we present NightSplitter, an on-line tool that is able to plan movie and dinner activities for a group of users, possibly splitting them in subgroups to...

Among the many open problems in the learning process, students dropout is one of the most complicated and negative ones, both for the student and the institutions, and being able to predict it could help to alleviate its social and economic costs. To address this problem we developed a tool that, by exploiting machine learning techniques,...

The Internet of Things (IoT) advocates for multi-layered platforms from edge devices to Cloud nodes where each layer adopts its own communication standards (media and data formats). While this freedom is optimal for in-layer communication, it puzzles cross-layer integration due to incompatibilities among standards. Also enforcing a unique...

Given a collection of algorithms, the Algorithm Selection (AS) problem consists in identifying which of them is the best one for solving a given problem. The selection depends on a set of numerical features that characterize the problem to solve. In this paper we show the impact of feature selection techniques on the performance of the SUNNY...

Given a collection of algorithms, the Algorithm Selection (AS) problem consists in identifying which of them is the best one for solving a given problem. In this paper we show how we adapted the algorithm selector SUNNY, originally tailored for constraint solving, to deal with general AS problems. Preliminary investigations based on the AS...

Multi-modal travelling is a common phenomenon. However, planning multi-modal journeys is still an unstructured and time-consuming experience for customers: they lose time assembling a comprehensive plan out of disparate data, spread over a multitude of information systems — each corresponding to a different company responsible for one of the...