Exploranative Code Quality Documents

Good code quality is a prerequisite for efficiently developing maintainable software. In this paper, we present a novel approach to generate exploranative (explanatory and exploratory) data-driven documents that report code quality in an interactive, exploratory environment. We employ a template-based natural language generation method to create textual explanations about the code quality, dependent on data from software metrics. The interactive document is enriched by different kinds of visualization, including parallel coordinates plots and scatterplots for data exploration and graphics embedded into text. We devise an interaction model that allows users to explore code quality with consistent linking between text and visualizations; through integrated explanatory text, users are taught background knowledge about code quality aspects. Our approach to interactive documents was developed in a design study process that included software engineering and visual analytics experts. Although the solution is specific to the software engineering scenario, we discuss how the concept could generalize to multivariate data and report lessons learned in a broader scope.Comment: IEEE VIS VAST 201

Proposal for the deployment of an augmented reality tool for construction safety inspection

The construction site is a hazardous place. The dynamic, complex interaction between workers, machinery, and the environment leads to dangerous risks. In response to such risks, the goal is to fulfill the zero accidents philosophy, which requires the development of safety skills among workers and the provision of tools for risk prevention. In pursuit of that vision, this work studies collective protective equipment (CPE). Traditional methodologies propose visual inspections using checklists, the effectiveness of which depends on the quality of the inspection by the safety advisor (SA). This paper analyses the traditional process of safety inspections in building projects: the traditional methods, main pain points, and bottlenecks are identified, along with the key performance indicators (KPIs) needed to complete these processes correctly. Because of this, a methodology that digitises the CPE inspection process is proposed. Augmented reality (AR) is used as a 3D viewer with an intuitive interface for the SA, and, accordingly, functional requirements are detailed and different information layers and user interfaces for AR applications are proposed. In addition, the workflow and KPIs are shown. To demonstrate the feasibility of the proposal, a proof of concept is developed and evaluated. The relevance of this work lies in providing background for the use of AR in safety inspection processes on construction sites and in offering methodological recommendations for the development and evaluation of these applications.This work has been supported by the Ministry of Science, Innovation and Universities of Spain (MICIU) through the BIMIoTICa project (RTC-2017-6454-7) and by the CONICYT for its economic support to Felipe Muñoz, beneficiary of a pre-doctoral grant (CONICYT—PCHA/International Doctorate/2019-72200306). The authors also acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness, through the “Severo Ochoa Centre of Excellence (2019–2023) under the grant CEX2018-000797-S funded by MCIN/AEI/10.13039/501100011033”.Peer ReviewedPostprint (published version

Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training

Training a state-of-the-art deep neural network (DNN) is a computationally-expensive and time-consuming process, which incentivizes deep learning developers to debug their DNNs for computational performance. However, effectively performing this debugging requires intimate knowledge about the underlying software and hardware systems---something that the typical deep learning developer may not have. To help bridge this gap, we present Skyline: a new interactive tool for DNN training that supports in-editor computational performance profiling, visualization, and debugging. Skyline's key contribution is that it leverages special computational properties of DNN training to provide (i) interactive performance predictions and visualizations, and (ii) directly manipulatable visualizations that, when dragged, mutate the batch size in the code. As an in-editor tool, Skyline allows users to leverage these diagnostic features to debug the performance of their DNNs during development. An exploratory qualitative user study of Skyline produced promising results; all the participants found Skyline to be useful and easy to use.Comment: 14 pages, 5 figures. Appears in the proceedings of UIST'2

Ubiquitous computing and natural interfaces for environmental information

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe next computing revolution‘s objective is to embed every street, building, room and object with computational power. Ubiquitous computing (ubicomp) will allow every object to receive and transmit information, sense its surroundings and act accordingly, be located from anywhere in the world, connect every person. Everyone will have the possibility to access information, despite their age, computer knowledge, literacy or physical impairment. It will impact the world in a profound way, empowering mankind, improving the environment, but will also create new challenges that our society, economy, health and global environment will have to overcome. Negative impacts have to be identified and dealt with in advance. Despite these concerns, environmental studies have been mostly absent from discussions on the new paradigm. This thesis seeks to examine ubiquitous computing, its technological emergence, raise awareness towards future impacts and explore the design of new interfaces and rich interaction modes. Environmental information is approached as an area which may greatly benefit from ubicomp as a way to gather, treat and disseminate it, simultaneously complying with the Aarhus convention. In an educational context, new media are poised to revolutionize the way we perceive, learn and interact with environmental information. cUbiq is presented as a natural interface to access that information

SI-Lab Annual Research Report 2020

The Signal & Images Laboratory (http://si.isti.cnr.it/) is an interdisciplinary research group in computer vision, signal analysis, smart vision systems and multimedia data understanding. It is part of the Institute for Information Science and Technologies of the National Research Council of Italy. This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2020