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Publicações

2025

Modelling sustainability in cyber-physical systems: A systematic mapping study

Autores
Barisic, A; Cunha, J; Ruchkin, I; Moreira, A; Araújo, J; Challenger, M; Savic, D; Amaral, V;

Publicação
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS

Abstract
Supporting sustainability through modelling and analysis has become an active area of research in Software Engineering. Therefore, it is important and timely to survey the current state of the art in sustainability in Cyber-Physical Systems (CPS), one of the most rapidly evolving classes of complex software systems. This work presents the findings of a Systematic Mapping Study (SMS) that aims to identify key primary studies reporting on CPS modelling approaches that address sustainability over the last 10 years. Our literature search retrieved 2209 papers, of which 104 primary studies were deemed relevant fora detailed characterisation. These studies were analysed based on nine research questions designed to extract information on sustainability attributes, methods, models/meta-models, metrics, processes, and tools used to improve the sustainability of CPS. These questions also aimed to gather data on domain-specific modelling approaches and relevant application domains. The final results report findings for each of our questions, highlight interesting correlations among them, and identify literature gaps worth investigating in the near future.

2025

Automated Social Media Feedback Analysis for Software Requirements Elicitation: A Case Study in the Streaming Industry

Autores
Silva, M; Faria, JP;

Publicação
Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2025, Porto, Portugal, April 4-6, 2025.

Abstract

2025

Automatic Generation of Loop Invariants in Dafny with Large Language Models

Autores
Faria, JP; Trigo, E; Abreu, R;

Publicação
Fundamentals of Software Engineering - 11th IFIP WG 2.2 International Conference, FSEN 2025, Västerås, Sweden, April 7-8, 2025, Proceedings

Abstract
Recent verification tools aim to make formal verification more accessible for software engineers by automating most of the verification process. However, the manual work and expertise required to write verification helper code, such as loop invariants and auxiliary lemmas and assertions, remains a barrier. This paper explores the use of Large Language Models (LLMs) to automate the generation of loop invariants for programs in Dafny. We tested the approach on a curated dataset of 100 programs in Dafny involving arrays, strings, and numeric types. Using a multimodel approach that combines GPT-4o and Claude 3.5 Sonnet, correct loop invariants (passing the Dafny verifier) were generated at the first attempt for 92% of the programs, and in at most five attempts for 95% of the programs. Additionally, we developed an extension to the Dafny plugin for Visual Studio Code to incorporate automatic loop invariant generation into the IDE. Our work stands out from related approaches by handling a broader class of problems and offering IDE integration. © IFIP International Federation for Information Processing 2025.

2025

Spatio-Temporal Predictive Modeling Techniques for Different Domains: a Survey

Autores
Kumar, R; Bhanu, M; Mendes-moreira, J; Chandra, J;

Publicação
ACM COMPUTING SURVEYS

Abstract
Spatio-temporal prediction tasks play a crucial role in facilitating informed decision-making through anticipatory insights. By accurately predicting future outcomes, the ability to strategize, preemptively address risks, and minimize their potential impact is enhanced. The precision in forecasting spatial and temporal patterns holds significant potential for optimizing resource allocation, land utilization, and infrastructure development. While existing review and survey papers predominantly focus on specific forecasting domains such as intelligent transportation, urban planning, pandemics, disease prediction, climate and weather forecasting, environmental data prediction, and agricultural yield projection, limited attention has been devoted to comprehensive surveys encompassing multiple objects concurrently. This article addresses this gap by comprehensively analyzing techniques employed in traffic, pandemics, disease forecasting, climate and weather prediction, agricultural yield estimation, and environmental data prediction. Furthermore, it elucidates challenges inherent in spatio-temporal forecasting and outlines potential avenues for future research exploration.

2025

A Deep Learning Framework for Medium-Term Covariance Forecasting in Multi-Asset Portfolios

Autores
Reis, P; Serra, AP; Gama, J;

Publicação
CoRR

Abstract

2025

Developing Strategies for Sustainable and Resilient Supply Chains

Autores
Zimmermann, R; Senna, P; Pereira, P; Fornasiero, R; Zangiacomi, A; Betto, F;

Publicação
HUMAN-CENTRED TECHNOLOGY MANAGEMENT FOR A SUSTAINABLE FUTURE, VOL 3, IAMOT 2024

Abstract
Although recent studies have recognised that sustainability and resilience should be considered part of the same efforts in the context of a transformative perspective, research combining both constructs is still scarce. This study adopts a comprehensive perspective that acknowledges that maintaining business continuity (through persisting, adapting or transforming), to reduce long-term risks is a common aspect of sustainability and resilience. It aims to identify strategies to be applied by companies and SCs in order to increase their social, environmental and economic sustainability, as well as their ability to be ready, respond and recover from unexpected events. Considering that the actions and strategies to deal with sustainability and resilience can be different and eventually paradoxical, this work applies the organizational ambidexterity approach as a theoretical background.

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