Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Facts & Numbers
000
Presentation

Advanced Computing Systems

At CRACS, our mission is to pursue scientific excellence in the areas of programming languages, parallel and distributed computing, security and privacy, information mining, and Web based systems with a focus on developing scalable software systems for challenging, multidisciplinary applications.

Our research environment is enriched with junior talented researchers that together with senior researchers build the necessary critical mass and scientific competences to fulfill the institution’s mission.

Latest News
Computer Science

Privacy in 6G networks can be a challenge: INESC TEC integrates European project focusing on protection

Future 6G networks should make data privacy a top priority. INESC TEC is part of PRIVATEER, a European project that aims to create a robust and decentralised AI-based security analysis for 6G networks. "Privacy" is the key word. 

13th June 2023

Computer Science

INESC TEC researchers acknowledged for research work aimed at protecting the privacy of mobile phones

A group of INESC TEC researchers was acknowledged due to their research work on the management of permissions on mobile devices. The team developed a set of techniques to automate the response to requests for permissions by smartphone applications, with a reliability of 90%. This work received the award for best scientific paper at the ACM CODASPY conference, which took place in the United States of America.

08th July 2022

Networked Intelligent Systems

INESC TEC part of project that will make autonomous vehicles safer

INESC TEC will contribute to the development of perception algorithms, computing and architectures based on artificial intelligence, within the scope of the project THEIA - Automated Perception Driving, a partnership between the University of Porto and Bosch - which aims to make autonomous vehicles safer through a better perception of the outside environment.

07th June 2022

Computer Science

INESC TEC developed a tool to identify biological species

INESC TEC researchers developed Biolens, a web application that allows the classification of biological species through the submission of photographs. Currently, the platform is able to recognise a significant subset of the Portuguese species of dragonflies, butterflies and moths.

03rd June 2022

Computer Science

INESC TEC researcher publishes book dedicated to gamification

Ricardo Queirós, researcher at INESC TEC, and professor at the School of Media Arts and Design of the Polytechnic of Porto (ESMAD-P.Porto), is one of the authors of the book Gamificação Aplicada às Organizações e ao Ensino, along with Mário Pinto, also a professor at ESMAD-P.Porto and a researcher at uniMAD.

24th March 2022

041

Featured Projects

PRIVATEER

Privacy-first Security Enablers for 6G Networks

2023-2025

THEIA

Automated Perception Driving

2022-2023

AI4DM

AI predictive modeling Services

2021-2022

FGPEPlus

Learning tools interoperability for gamified programming education

2021-2023

JuezLTI

Automatic assessment of computing exercises using LTI standard

2021-2023

PANDORA

Cyber Defence Platform for Real-time Threat Hunting, Incident Response and Information Sharing

2020-2022

Cortaderia

Desenvolvimento de Software para Monitorização da Espécie Invasora Cortaderia selloana

2020-2020

Authenticus19_20

Consultoria Tecnológica em Sistemas CRIS e Cálculo de APC

2019-2020

T4CDTKC

Training 4 Cotec, Digital Transformation Knowledge Challenge - Elaboração de Programa de Formação “CONHECER E COMPREENDER O DESAFIO DAS TECNOLOGIAS DE TRANSFORMAÇÃO DIGITAL”

2019-2021

Angerona

Privacy preserving IOT middleware

2018-2019

FGPE

Framework for Gamified Programming Education

2018-2021

AuthenticusNF

Desenvolvimento de Indicadores de Produção Científica Baseados no Authenticus

2018-2018

PGODISSEIA

Serviço de instalação e configuração de uma plataforma de autenticação, implementação de solução de gestão centralizada de certificados digitais, auditoria de segurança (pen-testing) e análise de impacto de privacidade dos tratamentos de dados pessoais das plataformas de integração e autenticação

2018-2020

CRADLE

Deep learning in cancer drug discovery: a pipeline for the generation of new therapies

2018-2021

Authenticus2019

Apoio Técnico ao CINTESIS para extração de indicadores de produção científica baseados no Authenticus

2018-2018

ELVEN

Elven - Expressive Logics for VErifying the Net

2016-2019

Digi-NewB

Non-invasive monitoring of perinatal health through multiparametric digital representation of clinically relevant functions for improving clinical intervention in neonatal units (Digi-NewB)

2016-2020

FOUREYES

TEC4Growth - RL FourEyes - Intelligence, Interaction, Immersion and Innovation for media industries

2015-2019

NanoStima-RL5

NanoSTIMA - Advanced Methodologies for Computer-Aided Detection and Diagnosis

2015-2019

NanoStima-RL3

NanoSTIMA - Health data infrastructure

2015-2019

NanoStima-RL4

NanoSTIMA - Health Data Analysis & Decision

2015-2019

SMILES

SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2019

FOTOCATGRAF

Graphene-based semiconductor photocatalysis for a safe and sustainable water supply: an advanced technology for emerging pollutants removal

2015-2018

REMINDS

Relevance Mining and Detection System (REMINDS)

2015-2017

PANF

Methods to retrieve and communicate data from Sifarma

2015-2016

SEA

SEA-Sistema de ensino autoadaptativo

2015-2015

MGI

Contrato de Aquisição de serviços de produção e desenvolvimento de módulo para gestão de iterações para integrar no sistema de informação da UP (SIGARRA)

2015-2015

Hyrax

Crowd-Sourcing Mobile Devices to Develop Edge Clouds

2014-2018

DAT

Curation and intelligent data analysis

2014-2015

ABLe

Advice-Based Learning for Health Care

2013-2015

Authenticus

Authenticus - System to Identify and Validate Portuguese Scientific Publications

2013-2016

SIBILA

Towards Smart Interacting Blocks that Improve Learned Advice

2013-2015

ADE

Adverse Drug Effects Detection

2012-2015

e-Policy

Engineering for the Policy-making Life Cycle (ePolicy)

2011-2014

Leap

Logic environments with Advanced Paralelism

2011-2014

MACAW

Macroprogramming for Wireless Sensor Networks

2011-2014

Breadcrumbs

Social network based on personal libraries of news fragments

2010-2012

Ofelia

Open Federated Environments Leveraging Identity and Authorization

2010-2013

Horus

Horn Representations of Uncertain Systems

2010-2013

DIGISCOPE

DIGItally enhanced stethosCOPE for clinical usage

2010-2013

Palco3.0

Intelligent Web system to support the management of a social network on music

2008-2011

Team
Publications

CRACS Publications

View all Publications

2023

PROGpedia: Collection of source-code submitted to introductory programming assignments

Authors
Paiva, JC; Leal, JP; Figueira, A;

Publication
DATA IN BRIEF

Abstract
Learning how to program is a difficult task. To acquire the re-quired skills, novice programmers must solve a broad range of programming activities, always supported with timely, rich, and accurate feedback. Automated assessment tools play a major role in fulfilling these needs, being a common pres-ence in introductory programming courses. As programming exercises are not easy to produce and those loaded into these tools must adhere to specific format requirements, teachers often opt for reusing them for several years. There-fore, most automated assessment tools, particularly Mooshak, store hundreds of submissions to the same programming ex-ercises, as these need to be kept after automatically pro-cessed for possible subsequent manual revision. Our dataset consists of the submissions to 16 programming exercises in Mooshak proposed in multiple years within the 2003-2020 timespan to undergraduate Computer Science students at the Faculty of Sciences from the University of Porto. In particular, we extract their code property graphs and store them as CSV files. The analysis of this data can enable, for instance, the generation of more concise and personalized feedback based on similar accepted submissions in the past, the identifica-tion of different strategies to solve a problem, the under -standing of a student's thinking process, among many other findings.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

2023

A WebApp for Reliability Detection in Social Media

Authors
David, F; Guimaraes, N; Figueira, A;

Publication
Procedia Computer Science

Abstract

2023

Bibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight into Feedback

Authors
Paiva, JC; Figueira, A; Leal, JP;

Publication
ELECTRONICS

Abstract
Learning to program requires diligent practice and creates room for discovery, trial and error, debugging, and concept mapping. Learners must walk this long road themselves, supported by appropriate and timely feedback. Providing such feedback in programming exercises is not a humanly feasible task. Therefore, the early and steadily growing interest of computer science educators in the automated assessment of programming exercises is not surprising. The automated assessment of programming assignments has been an active area of research for over a century, and interest in it continues to grow as it adapts to new developments in computer science and the resulting changes in educational requirements. It is therefore of paramount importance to understand the work that has been performed, who has performed it, its evolution over time, the relationships between publications, its hot topics, and open problems, among others. This paper presents a bibliometric study of the field, with a particular focus on the issue of automatic feedback generation, using literature data from the Web of Science Core Collection. It includes a descriptive analysis using various bibliometric measures and data visualizations on authors, affiliations, citations, and topics. In addition, we performed a complementary analysis focusing only on the subset of publications on the specific topic of automatic feedback generation. The results are highlighted and discussed.

2023

An NLP Approach to Understand the Top Ranked Higher Education Institutions’ Social Media Communication Strategy

Authors
Figueira, A; Nascimento, L;

Publication
Web Information Systems and Technologies

Abstract

2023

On the Quality of Synthetic Generated Tabular Data

Authors
Espinosa, E; Figueira, A;

Publication
MATHEMATICS

Abstract
Class imbalance is a common issue while developing classification models. In order to tackle this problem, synthetic data have recently been developed to enhance the minority class. These artificially generated samples aim to bolster the representation of the minority class. However, evaluating the suitability of such generated data is crucial to ensure their alignment with the original data distribution. Utility measures come into play here to quantify how similar the distribution of the generated data is to the original one. For tabular data, there are various evaluation methods that assess different characteristics of the generated data. In this study, we collected utility measures and categorized them based on the type of analysis they performed. We then applied these measures to synthetic data generated from two well-known datasets, Adults Income, and Liar+. We also used five well-known generative models, Borderline SMOTE, DataSynthesizer, CTGAN, CopulaGAN, and REaLTabFormer, to generate the synthetic data and evaluated its quality using the utility measures. The measurements have proven to be informative, indicating that if one synthetic dataset is superior to another in terms of utility measures, it will be more effective as an augmentation for the minority class when performing classification tasks.

Facts & Figures

7Proceedings in indexed conferences

2020

17Academic Staff

2020

59Researchers

2016