Terms extractions: an approach for requirements reuse

This paper presents a solution to a requirements reuse problem that utilises natural language processing and information retrieval technique. We proposed a semi-automated approach to extract the software features from online software review to assist the process to reuse natural language requirements. We have conducted an experiment to compare the manual feature extraction versus the semi-automated feature extraction. We used compilations of software review from the Internet as a source of this extraction process. The extracted software features are compared against the features obtained manually by human and the evaluation results obtained in terms of time, precision, recall, and F-Measure indicate a promising result

Mobile app and app store analysis, testing and optimisation

This talk presents results on analysis and testing of mobile apps and app stores, reviewing the work of the UCL App Analysis Group (UCLappA) on App Store Mining and Analysis. The talk also covers the work of the UCL CREST centre on Genetic Improvement, applicable to app improvement and optimisation

Metaheurísticas, búsqueda estocástica y cómputo eficiente en optimización aplicada

Las metaheurísticas son técnicas de optimización y resolución de problemas computacionales que toman inicialmente una solución factible, la cual es luego mejorada usando procedimientos heurísticos conocidos, como recocido simulado, algoritmos genéticos, búsqueda tabú y redes neuronales. La búsqueda estocástica está presente en estos métodos y su importancia reside en ser una herramienta general de optimización cuyo estudio puede aportar mejoras para las metaheurísticas y desarrollar variantes de ellas. Este proyecto propone estudiar propiedades teóricas y prácticas de estas técnicas y su aplicación en los problemas en los que trabajan sus integrantes, brindando metodologías para incrementar la eficiencia de los algoritmos involucrados y la confiabilidad de los resultados que producen. Estas metodologías aprovechan los avances en los métodos y técnicas de la computación eficiente y del cómputo en paralelo para desarrollar los algoritmos necesarios para validar las nuevas propuestas mediante casos de experimentación. La implementación de los algoritmos que permiten realizar las experiencias requiere la utilización de técnicas de las ciencias de los datos, del cómputo de alto rendimiento y métodos del campo de la optimización.Eje: Agentes y sistemas inteligentes.Red de Universidades con Carreras en Informátic

Tracking users' behaviors through real-time information in BIMs: Workflow for interconnection in the Brescia Smart Campus Demonstrator

An intelligent building supports the needs of its occupants by data analytics. Nowadays, buildings are evolving from being products to become effective service providers for end-users: thus, occupancy topics become crucial. The paper focuses on building operations, pointing out how advantages in supporting the needs of users could be derived through the implementation of Building Management Systems (BMS) into a Building Information Modeling (BIM) environment, connecting real-time information collected by sensors to a BIM database. The connection and the integration of information between BIM and BMS have been established based on the Industry Foundation Classes (IFC) neutral data format; moreover, web-interfaces and apps have been tested for enhancing information to be visualized by different end-users. The ongoing research has a twofold scope: 1) to point-out how buildings should evolve, managing knowledge coming from sensors in order to anticipate the needs of users, and 2) to analyze whether and how the centrality of users should change the building process. The proposed workflow has been tested on the Brescia Smart Campus Demonstrator, a building equipped with 94 off-the-shelf sensors