Eletti il Presidente e il Vice Presidente del CINI

L’Assemblea del Consorzio Interuniversitario Nazionale per l’Informatica (CINI) ha eletto Presidente il prof. Stefano Russo dell’Università degli Studi di Napoli Federico II.

Leggi

logo cnl

National Interuniversity Consortium for Informatics

CINI is the main point of reference for the Italian national academic research in the fields of Computer Science, Computer Engineering, and Information Technology. In a very strict cooperation with the national scientific communities, the Consortium promotes and coordinates scientific activities of research and technological transfer, both basic and applicative, in several fields of Computer Science and Computer Engineering.
Read
 

National Interuniversity Consortium for Informatics

The Consortium involves 1,300+ professors of both Computer Science (Italian SSD INF/01) and Computer Engineering (Italian SSD ING-INF/05), belonging to 39 public universities. The Consortium is submitted to the periodic Quality Evaluation of its research activities by ANVUR, the Italian National Agency for the Evaluation of the University System and Research.
Read
 

Press Review

Notifications (to archive) 

Calls For Papers & Other Opportunities

Wednesday 18 January 2017,

Exploiting machine learning techniques in software development processes

 

Ing. Domenico Amalfitano

 

University of Naples Federico II, Naples, Italy

Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione

 

Commonly used software systems integrate more often machine learning applications. For having an evidence of this, we can just consider few examples of software systems used in our everyday life. Among them, we may take into account the voice recognition and natural language systems that are present in almost all mobile devices released in recent years, or the recommendation systems exploited by Amazon to suggest the research contents on the basis of the type of users. Machine learning techniques are also implemented in critical software systems, such as the Advanced Driver Assistance Systems (ADAS) or the information security systems. In software engineering, machine learning techniques are more and more exploited for the quality improvement of the software development processes, mainly because their application allows to increase the efficiency of such processes. More specifically, these techniques allow to fully or partially automate some of the time consuming and error prone activities that usually require a great manual effort. In software engineering, machine learning techniques are more and more exploited for the quality improvement of the software development processes, mainly because their application allows to increase the efficiency of such processes. More specifically, these techniques allow to fully or partially automate some of the time consuming and error prone activities that usually require a great manual effort.

 

Wednesday 18 January 2017, Time: 11.00-13.00

Laboratorio CINI ITeM

Edificio Centri Comuni @ Complesso Universitario Monte S. Angelo

Via Cinthia, 21 80126

Attachments:
Download this file (locandina seminario cini item.pdf)Locandina

Share This

Horizon 2020

Logo Horizon 2020

CINI participates as expert delegate in the italian committee of the Horizon 2020 Program for Information and Communication Technologies

 

 

Institutional links

S5 Box

Cini Single Sign ON

This site only stores technical/functional cookies. If you want to know more, go to the Cookie Policy section.