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Apresentação

Laboratório de Software Confiável

No Laboratório de Software Confiável (HASLab), melhorando a prática através da teoria, criamos e implementamos software que vai além da funcionalidade: garantimos que é correto, resiliente e seguro contra falhas e ataques.


A nossa equipa de investigadores, cientistas e engenheiros tem competências em engenharia de software, onde desenvolvemos métodos e ferramentas para conceber e integrar software robusto; sistemas distribuídos, onde exploramos a distribuição e replicação para garantir escalabilidade e confiabilidade; e segurança da informação, onde considerando também os desafios da cibersegurança, fortalecemos os sistemas com protocolos criptográficos avançados e seguros, minimizando vulnerabilidades.


Com uma abordagem multidisciplinar e sustentada por princípios teóricos sólidos, criamos soluções inovadoras para software crítico, infraestruturas cloud seguras e gestão de big data com privacidade, impulsionando avanços científicos, inovação e consultoria de excelência.


Além disso, complementamos a nossa expertise em áreas como interação humano-computador, linguagens de programação, matemática de computação e computação quântica - porque acreditamos que o futuro do software confiável se constrói com conhecimento e inovação.

Tópicos
de interesse
081

Projetos em destaque

POISE

Programmable Asynchronous Asymmetric Secure Choreographies

2026-2027

QUANTHOS

QUANTHOS - Fotónica Integrada Topológica Quântica

2026-2027

Rescueware

Cibersegurança e Recuperação de Dados Inteligente e Auto-Configurável para a Resiliência contra Ransomware

2026-2029

HPCTRAIN

EuroHPC traineeships in Hosting Entities, Centres of Excellence and Competence Centres, SMEs and Industry

2026-2029

ADAPQO

Adaptive Query Optimization Architectures to Support Heterogeneous Data Intensive Applications

2025-2026

QuantumCLP

Quantum computing optimization for container loading problems: a new frontier in logistics optimization

2025-2027

BANSKY

A paraconsistent inference engine to support research in age-ralated molecular degeneration

2025-2028

JasminCode

Developing Reliable High-performance Assembly Code using Jasmin

2025-2026

TestBed5G_Robotics

Piloto de Robótica Móvel e Cibersegurança em Ambientes Industriais sobre Comunicações 5G – Europneumaq

2025-2026

ATAI

Aplicação de técnicas avançadas na gestão de escalas

2025-2027

BringTrust

Strengthening CI/CD Pipeline Cybersecurity and Safeguarding the Intellectual Property

2025-2028

SafeIaC

SafeIaC: Reliable Analysis and Automated Repair for Infrastructure as Code

2025-2028

PFAI4_6eD

Programa de Formação Avançada Industria 4 - 6a edição

2025-2025

INSIEME

Integrated Network for data Space and Interoperable Energy Management in Europe

2025-2028

DisaggregatedHPC

Towards energy-efficient, software-managed resource disaggregation in HPC infrastructures

2025-2026

InfraGov

InfraGov: A Public Framework for Reliable and Secure IT Infrastructure

2025-2026

VeriFixer

VeriFixer: Automated Repair for Verification-Aware Programming Languages

2025-2026

JRCSIF

JRC Interoperability Laboratory Adoption of the Semantic Interoperability Framework

2025-2025

CDMS

Claim Denial Management Solution

2025-2026

BolsasFCT_Gestao

Financiamento Bolsas Doutoramento FCT - Gestão

2025-9999

ENSCOMP4

Ensino de Ciência da Computação nas Escolas 4

2024-2026

PeT

PeT - Privacidade e Transparência

2024-2028

PFAI4_5eD

Programa de Formação Avançada Industria 4 - 5a edição

2024-2024

exaSIMPLE

exaSIMPLE: A Hybrid ML-CFD SIMPLE Algorithm for the Exascale Era

2024-2025

EPICURE

High-level specialised application support service in High-Performance Computing (HPC)

2024-2028

BCDSM

BCD.S+M - Sistema Modular de Armazenamento e Gestão de Dados em Blockchain com IA

2024-2027

TwinEU

Digital Twin for Europe

2024-2026

HEDGE_IoT

Holistic Approach towards Empowerment of the DiGitalization of the Energy Ecosystem through adoption of IoT solutions

2024-2027

HANAMI

Hpc AlliaNce for Applications and supercoMputing Innovation: the Europe - Japan collaboration

2024-2027

PFAI4_4eD

Programa de Formação Avançada Industria 4 - 4a edição

2023-2023

QuantELM

QuantELM: from Ultrafast optical processors to Quantum Extreme Learning Machines with integrated optics

2023-2024

ATE

Aliança para a Transição Energética

2023-2026

Green_Dat_AI

Energy-efficient AI-ready Data Spaces

2023-2025

EuroCC2

National Competence Centres in the framework of EuroHPC Phase 2

2023-2026

AURORA

Deteção de atividade no interior do veículo

2022-2023

ATTRACT_DIH

Digital Innovation Hub for Artificial Intelligence and High-Performance Computing

2022-2026

NewSpacePortugal

Agenda New Space Portugal

2022-2026

BeFlexible

Boosting engagement to increase flexibility

2022-2026

ENERSHARE

European commoN EneRgy dataSpace framework enabling data sHaring-driven Across- and beyond- eneRgy sErvices

2022-2025

Gridsoft

Parecer sobre a implementação de software para redes elétricas inteligentes

2022-2022

PFAI4_3ed

Programa de Formação Avançada Industria 4 - 3a edição

2022-2022

THEIA

Automated Perception Driving

2022-2023

IBEX

Métodos quantitativos para a programação ciber-física: Uma abordagem precisa para racicionar sobre imprecisões na computação ciber-física

2022-2025

SpecRep

Constraint-based Specification Repair

2022-2023

FLEXCOMM

Towards Energy-aware Communications: Connecting the power grid and communication infrastructure

2022-2023

IDINA

Identidade Digital Inclusiva Não Autoritativa

2021-2025

Sustainable HPC

Computação de elevado desempenho sustentável

2021-2025

CircThread

Building the Digital Thread for Circular Economy Product, Resource & Service Management

2021-2025

PassCert

Investigação do Impacto de Verificação Formal na Adopção de Software para Segurança de Passwords

2021-2022

IoT4Distribuicao

Análise de Requisitos e Especificação Funcional de uma Arquitetura Distribuída baseada em soluções IoT para a Gestão e Controlo da Rede de Distribuição

2021-2023

RISC2

A network for supporting the coordination of High-Performance Computing research between Europe and Latin America

2021-2023

DigiLightRail

Solução de Automação do Ciclo de Vida de Projectos de Sinalização Ferroviária

2020-2023

PFAI4.0

Programa de Formação Avançada Industria 4.0

2020-2021

PAStor

Programmable and Adaptable Storage for AI-oriented HPC Ecosystems

2020-2021

ACTPM

Automating Crash-Consistency Testing for Persistent Memory

2020-2021

AIDA

Adaptive, Intelligent and Distributed Assurance Platform

2020-2023

BigHPC

2020-2023

SLSNA

Prestação de Serviços no ambito do projeto SKORR

2020-2021

InterConnect

Interoperable Solutions Connecting Smart Homes, Buildings and Grids

2019-2024

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

CLOUD4CANDY

Cloud for CANDY

2019-2019

HADES

Sistemas descentralizados confiáveis e escaláveis suportados por hardware

2018-2022

MaLPIS

Aprendizagem Automática para Deteção de Ataques e Identificação de Perfis Segurança na Internet

2018-2022

SKORR

Advancing the Frontier of Social Media Management Tools

2018-2021

DaVinci

Architecturas distribuídas: variabilidade e interação de sistemas ciber-físicos

2018-2022

SAFER

Verificação de segurança para software robótico

2018-2021

KLEE

Modelação coalgébrica e análise para biologia sintética computacional

2018-2021

InteGrid

Demonstration of INTElligent grid technologies for renewables INTEgration and INTEractive consumer participation enabling INTEroperable market solutions and INTErconnected stakeholders

2017-2020

Lightkone

Lightweight Computation for Networks at the Edge

2017-2019

CloudDBAppliance

European Cloud In-Memory Database Appliance with Predictable Performance for Critical Applications

2016-2019

Cloud-Setup

PLATAFORMA DE PREPARAÇÃO DE CONTEÚDOS AUDIOVISUAIS PARA INGEST NA CLOUD

2016-2019

GSL

GreenSoftwareLab: Computação Verde como uma Disciplina de Engenharia

2016-2019

CORAL-TOOLS

CORAL - Sustainable Ocean Exploitation: Tools and Sensors

2016-2018

SafeCloud

Secure and Resilient Cloud Architecture

2015-2018

NanoStima-RL1

NanoSTIMA - Macro-to-Nano Human Sensing Technologies

2015-2019

NanoStima-RL3

NanoSTIMA - Health data infrastructure

2015-2019

SMILES

TEC4Growth - RL SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2019

UPGRID

Real proven solutions to enable active demand and distributed generation flexible integration, through a fully controllable LOW Voltage and medium voltage distribution grid

2015-2017

LeanBigData

Análise Integrada e Visual de Big Data Ultra-escalável e Ultra-eficiente

2014-2017

Practice

Ferramentas de Preservação de Privacidade na Cloud

2013-2016

CoherentPaaS

PaaS Rica e Coerente com um Modelo de Programação Comum

2013-2016

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Publicações

HASLab Publicações

Ler todas as publicações

2025

Rethinking BFT: Leveraging Diverse Software Components with LLMs

Autores
Imperadeiro, J; Alonso, AN; Pereira, J;

Publicação
2025 55TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS-SUPPLEMENTAL VOLUME, DSN-S

Abstract
Diversity is crucial in systems that tolerate Byzantine faults. Traditionally, system builders have relied on standardized interfaces (e.g., POSIX for operating systems) to obtain off-the-shelf components or on n-version programming for custom functionality. Unfortunately, standardized alternatives are rare, and the independent development of multiple versions of the same software is costly and justified only on the most critical applications. In this paper, we show that a limited and focused use of LLMs for translation opens up the possibility of leveraging the existing diversity in functionally equivalent but non-standardized components. Specifically, we show that LLMs can produce functionally correct database query translations with minimal guidance and adapt to diverse data models and query contexts, enabling the use of radically different database models, both SQL and NoSQL, together in a Byzantine fault-tolerant replicated system. We outline an approach to achieve this in practice and discuss future research directions.

2025

Towards Adaptive Transactional Consistency for Georeplicated Datastores

Autores
Braga, R; Pereira, J; Coelho, F;

Publicação
40TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING

Abstract
Developers of data-intensive georeplicated applications face a difficult decision when selecting a database system. As captured by the CAP theorem, CP systems such as Spanner provide strong consistency that greatly simplifies application development. AP systems such as AntidoteDB providing Transactional Causal Consistency (TCC), ensure availability in face of network partitions and isolate performance from wide-area round-trip times, but avoid lost-update anomalies only when values can be merged. Ideally, an application should be able to adapt to current data and network conditions by selecting which transactional consistency to use for each transaction. In this paper, we test the hypothesis that a georeplicated database system can be built at its core providing only TCC, hence, being AP, but allow an application to execute some transactions under Snapshot Isolation (SI), hence CP. Our main result is showing that this can be achieved even when all the interaction happens through the TCC database system, without additional communication channels between the participants. A preliminary experimental evaluation with a proof-of-concept implementation using AntidoteDB shows that this approach is feasible.

2025

CRDV: Conflict-free Replicated Data Views

Autores
Faria, N; Pereira, J;

Publicação
Proc. ACM Manag. Data

Abstract
There are now multiple proposals for Conflict-free Replicated Data Types (CRDTs) in SQL databases aimed at distributed systems. Some, such as ElectricSQL, provide only relational tables as convergent replicated maps, but this omits semantics that would be useful for merging updates. Others, such as Pg\_crdt, provide access to a rich library of encapsulated column types. However, this puts merge and query processing outside the scope of the query optimizer and restricts the ability of an administrator to influence access paths with materialization and indexes. Our proposal, CRDV, overcomes this challenge by using two layers implemented as SQL views: The first provides a replicated relational table from an update history, while the second implements varied and rich types on top of the replicated table. This allows the definition of merge semantics, or even entire new data types, in SQL itself, and enables global optimization of user queries together with merge operations. Therefore, it naturally extends the scope of query optimization and local transactions to operations on replicated data, can be used to reproduce the functionality of common CRDTs with simple SQL idioms, and results in better performance than alternatives.

2025

BLADE - Byzantine-tolerant Learning under an Asynchronous and Decentralized Environment

Autores
Ferreira, G; Alonso, AN; Pereira, J;

Publicação
2025 20TH EUROPEAN DEPENDABLE COMPUTING CONFERENCE COMPANION PROCEEDINGS, EDCC-C

Abstract
Machine learning models are growing, with some large language models reaching a scale of billions of trainable parameters. Training these models has since become one of the most data-hungry and computation-heavy tasks. Efforts to distribute the training task mostly follow a federated approach, where a central server oversees the training process. This approach: 1) raises concerns about data privacy; and 2) creates a single point of failure. Current proposals for a fully decentralized approach often rely on costly broadcasts to disseminate model updates and do not tolerate heterogeneity in the training data, as it makes detecting Byzantine contributions harder. We propose BLADE, a generalized fully decentralized (and asynchronous) Byzantine fault-tolerant machine learning algorithm. BLADE was designed to be configurable and adapt to harsh environments, and significantly reduces the communication overhead compared to the state of the art. We performed a comprehensive empirical evaluation, and results confirm models trained with BLADE can achieve an accuracy comparable to a centralized training instance, even if the data distribution among peers is heterogeneous, and robustly aggregate model updates in the presence of Byzantine attacks, and even against sporadic Byzantine majorities.

2025

Exploring a Quantum Programming Language with Concurrency

Autores
Jain, M; Fernandes, V; Madeira, A; Barbosa, LS;

Publicação
Programming

Abstract