8 Search Results for "Carvalho, João Paulo"

Document
DOI: 10.4230/OASIcs.ICPEC.2025.2
Enabling Secure Coding: Exploring GenAI for Developer Training and Education

Authors: Sathwik Amburi, Tiago Espinha Gasiba, Ulrike Lechner, and Maria Pinto-Albuquerque

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)

Abstract
The rapid adoption of GenAI for code generation presents unprecedented opportunities and significant security challenges. Raising awareness about secure coding is critical for preventing software vulnerabilities. To investigate how Generative AI can best support secure coding, we built an AI Secure Coding platform, an interactive training environment that embeds a GPT-4 based chatbot directly into a structured challenge workflow. The platform comprises a landing page, a challenges page with three AI-generated tasks, and a challenge page where participants work with code snippets. In each challenge, developers (1) identify vulnerabilities by reviewing code and adding comments, (2) ask the AI for help via a chat based interface, (3) review and refine comments based on AI feedback, and (4) fix vulnerabilities by submitting secure patches. The study involved 18 industry developers tackling three challenges. Participants used the AI Secure Coding Platform to detect and remediate vulnerabilities and then completed a survey to capture their opinions and comfort level with AI assisted platform for secure coding. Results show that AI assistance can boost productivity, reduce errors, and uncover more defects when treated as a "second pair of eyes," but it can also foster over-reliance. This study introduces the AI Secure Coding platform, presents preliminary results from a initial study, and shows that embedding GenAI into a structured secure-coding workflow can both enable and challenge developers. This work also opens the door to a new research field: leveraging GenAI to enable secure software development.
Cite as

Sathwik Amburi, Tiago Espinha Gasiba, Ulrike Lechner, and Maria Pinto-Albuquerque. Enabling Secure Coding: Exploring GenAI for Developer Training and Education. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{amburi_et_al:OASIcs.ICPEC.2025.2,
  author =	{Amburi, Sathwik and Espinha Gasiba, Tiago and Lechner, Ulrike and Pinto-Albuquerque, Maria},
  title =	{{Enabling Secure Coding: Exploring GenAI for Developer Training and Education}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{2:1--2:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.2},
  URN =		{urn:nbn:de:0030-drops-240321},
  doi =		{10.4230/OASIcs.ICPEC.2025.2},
  annote =	{Keywords: Secure Coding, Industry, Software Development, Generative AI, Large Language Models, Teaching}
}
Document
Survey
DOI: 10.4230/TGDK.3.1.3
Uncertainty Management in the Construction of Knowledge Graphs: A Survey

Authors: Lucas Jarnac, Yoan Chabot, and Miguel Couceiro

Published in: TGDK, Volume 3, Issue 1 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 1

Abstract
Knowledge Graphs (KGs) are a major asset for companies thanks to their great flexibility in data representation and their numerous applications, e.g., vocabulary sharing, Q&A or recommendation systems. To build a KG, it is a common practice to rely on automatic methods for extracting knowledge from various heterogeneous sources. However, in a noisy and uncertain world, knowledge may not be reliable and conflicts between data sources may occur. Integrating unreliable data would directly impact the use of the KG, therefore such conflicts must be resolved. This could be done manually by selecting the best data to integrate. This first approach is highly accurate, but costly and time-consuming. That is why recent efforts focus on automatic approaches, which represent a challenging task since it requires handling the uncertainty of extracted knowledge throughout its integration into the KG. We survey state-of-the-art approaches in this direction and present constructions of both open and enterprise KGs. We then describe different knowledge extraction methods and discuss downstream tasks after knowledge acquisition, including KG completion using embedding models, knowledge alignment, and knowledge fusion in order to address the problem of knowledge uncertainty in KG construction. We conclude with a discussion on the remaining challenges and perspectives when constructing a KG taking into account uncertainty.
Cite as

Lucas Jarnac, Yoan Chabot, and Miguel Couceiro. Uncertainty Management in the Construction of Knowledge Graphs: A Survey. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 1, pp. 3:1-3:48, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{jarnac_et_al:TGDK.3.1.3,
  author =	{Jarnac, Lucas and Chabot, Yoan and Couceiro, Miguel},
  title =	{{Uncertainty Management in the Construction of Knowledge Graphs: A Survey}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:48},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.1.3},
  URN =		{urn:nbn:de:0030-drops-233733},
  doi =		{10.4230/TGDK.3.1.3},
  annote =	{Keywords: Knowledge reconciliation, Uncertainty, Heterogeneous sources, Knowledge graph construction}
}
Document
Position
DOI: 10.4230/TGDK.1.1.5
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities

Authors: Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and graph-structured. The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with the ultimate aim to advance scientific discovery. In this survey and position paper, we discuss recent developments and advances in the use of graph-based technologies in life sciences and set out a vision for how these technologies will impact these fields into the future. We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial intelligence applications to support explanations (explainable AI). We select a few exemplary use cases for each topic, discuss the challenges and open research questions within these topics, and conclude with a perspective and outlook that summarizes the overarching challenges and their potential solutions as a guide for future research.
Cite as

Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma. Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 5:1-5:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{chen_et_al:TGDK.1.1.5,
  author =	{Chen, Jiaoyan and Dong, Hang and Hastings, Janna and Jim\'{e}nez-Ruiz, Ernesto and L\'{o}pez, Vanessa and Monnin, Pierre and Pesquita, Catia and \v{S}koda, Petr and Tamma, Valentina},
  title =	{{Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:33},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.5},
  URN =		{urn:nbn:de:0030-drops-194791},
  doi =		{10.4230/TGDK.1.1.5},
  annote =	{Keywords: Knowledge graphs, Life science, Knowledge discovery, Explainable AI}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2023.9
NLP/AI Based Techniques for Programming Exercises Generation

Authors: Tiago Carvalho Freitas, Alvaro Costa Neto, Maria João Varanda Pereira, and Pedro Rangel Henriques

Published in: OASIcs, Volume 112, 4th International Computer Programming Education Conference (ICPEC 2023)

Abstract
This paper focuses on the enhancement of computer programming exercises generation to the benefit of both students and teachers. By exploring Natural Language Processing (NLP) and Machine Learning (ML) methods for automatic generation of text and source code, it is possible to semi-automatically construct programming exercises, aiding teachers to reduce redundant work and more easily apply active learning methodologies. This would not only allow them to still play a leading role in the teaching-learning process, but also provide students a better and more interactive learning experience. If embedded in a widely accessible website, an exercises generator with these Artificial Intelligence (AI) methods might be used directly by students, in order to obtain randomised lists of exercises for their own study, at their own time. The emergence of new and increasingly powerful technologies, such as the ones utilised by ChatGPT, raises the discussion about their use for exercise generation. Albeit highly capable, monetary and computational costs are still obstacles for wider adoption, as well as the possibility of incorrect results. This paper describes the characteristics and behaviour of several ML models applied and trained for text and code generation and their use to generate computer programming exercises. Finally, an analysis based on correctness and coherence of the resulting exercise statements and complementary source codes generated/produced is presented, and the role that this type of technology can play in a programming exercise automatic generation system is discussed.
Cite as

Tiago Carvalho Freitas, Alvaro Costa Neto, Maria João Varanda Pereira, and Pedro Rangel Henriques. NLP/AI Based Techniques for Programming Exercises Generation. In 4th International Computer Programming Education Conference (ICPEC 2023). Open Access Series in Informatics (OASIcs), Volume 112, pp. 9:1-9:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{freitas_et_al:OASIcs.ICPEC.2023.9,
  author =	{Freitas, Tiago Carvalho and Costa Neto, Alvaro and Pereira, Maria Jo\~{a}o Varanda and Henriques, Pedro Rangel},
  title =	{{NLP/AI Based Techniques for Programming Exercises Generation}},
  booktitle =	{4th International Computer Programming Education Conference (ICPEC 2023)},
  pages =	{9:1--9:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-290-7},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{112},
  editor =	{Peixoto de Queir\'{o}s, Ricardo Alexandre and Teixeira Pinto, M\'{a}rio Paulo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2023.9},
  URN =		{urn:nbn:de:0030-drops-185058},
  doi =		{10.4230/OASIcs.ICPEC.2023.9},
  annote =	{Keywords: Natural Language Processing, Computer Programming Education, Exercises Generation, Text Generation, Code Generation}
}
Document
DOI: 10.4230/OASIcs.SLATE.2014.19
Conclave: Writing Programs to Understand Programs

Authors: Nuno Ramos Carvalho, José João Almeida, Maria João Varanda Pereira, and Pedro Rangel Henriques

Published in: OASIcs, Volume 38, 3rd Symposium on Languages, Applications and Technologies (2014)

Abstract
Software maintainers are often challenged with source code changes to improve software systems, or eliminate defects, in unfamiliar programs. To undertake these tasks a sufficient understanding of the system, or at least a small part of it, is required. One of the most time consuming tasks of this process is locating which parts of the code are responsible for some key functionality or feature. This paper introduces Conclave, an environment for software analysis, that enhances program comprehension activities. Programmers use natural languages to describe and discuss the problem domain, programming languages to write source code, and markup languages to have programs talking with other programs, and so this system has to cope with this heterogeneity of dialects, and provide tools in all these areas to effectively contribute to the understanding process. The source code, the problem domain, and the side effects of running the program are represented in the system using ontologies. A combination of tools (specialized in different kinds of languages) create mappings between the different domains. Conclave provides facilities for feature location, code search, and views of the software that ease the process of understanding the code, devising changes. The underlying feature location technique explores natural language terms used in programs (e.g. function and variable names); using textual analysis and a collection of Natural Language Processing techniques, computes synonymous sets of terms. These sets are used to score relatedness between program elements, and search queries or problem domain concepts, producing sorted ranks of program elements that address the search criteria, or concepts respectively.
Cite as

Nuno Ramos Carvalho, José João Almeida, Maria João Varanda Pereira, and Pedro Rangel Henriques. Conclave: Writing Programs to Understand Programs. In 3rd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 38, pp. 19-34, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{carvalho_et_al:OASIcs.SLATE.2014.19,
  author =	{Carvalho, Nuno Ramos and Almeida, Jos\'{e} Jo\~{a}o and Pereira, Maria Jo\~{a}o Varanda and Henriques, Pedro Rangel},
  title =	{{Conclave: Writing Programs to Understand Programs}},
  booktitle =	{3rd Symposium on Languages, Applications and Technologies},
  pages =	{19--34},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-68-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{38},
  editor =	{Pereira, Maria Jo\~{a}o Varanda and Leal, Jos\'{e} Paulo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2014.19},
  URN =		{urn:nbn:de:0030-drops-45561},
  doi =		{10.4230/OASIcs.SLATE.2014.19},
  annote =	{Keywords: software maintenance, software evolution, program comprehension, feature location, concept location, natural language processing}
}
Document
DOI: 10.4230/OASIcs.SLATE.2014.185
Detecting a Tweet’s Topic within a Large Number of Portuguese Twitter Trends

Authors: Hugo Rosa, João Paulo Carvalho, and Fernando Batista

Published in: OASIcs, Volume 38, 3rd Symposium on Languages, Applications and Technologies (2014)

Abstract
In this paper we propose to approach the subject of Twitter Topic Detection when in the presence of a large number of trending topics. We use a new technique, called Twitter Topic Fuzzy Fingerprints, and compare it with two popular text classification techniques, Support Vector Machines (SVM) and k-Nearest Neighbours (kNN). Preliminary results show that it outperforms the other two techniques, while still being much faster, which is an essential feature when processing large volumes of streaming data. We focused on a data set of Portuguese language tweets and the respective top trends as indicated by Twitter.
Cite as

Hugo Rosa, João Paulo Carvalho, and Fernando Batista. Detecting a Tweet’s Topic within a Large Number of Portuguese Twitter Trends. In 3rd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 38, pp. 185-199, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{rosa_et_al:OASIcs.SLATE.2014.185,
  author =	{Rosa, Hugo and Carvalho, Jo\~{a}o Paulo and Batista, Fernando},
  title =	{{Detecting a Tweet’s Topic within a Large Number of Portuguese Twitter Trends}},
  booktitle =	{3rd Symposium on Languages, Applications and Technologies},
  pages =	{185--199},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-68-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{38},
  editor =	{Pereira, Maria Jo\~{a}o Varanda and Leal, Jos\'{e} Paulo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2014.185},
  URN =		{urn:nbn:de:0030-drops-45696},
  doi =		{10.4230/OASIcs.SLATE.2014.185},
  annote =	{Keywords: topic detection, social networks data mining, Twitter, Portuguese language}
}
Document
DOI: 10.4230/OASIcs.SLATE.2014.275
Expanding a Database of Portuguese Tweets

Authors: Gaspar Brogueira, Fernando Batista, João Paulo Carvalho, and Helena Moniz

Published in: OASIcs, Volume 38, 3rd Symposium on Languages, Applications and Technologies (2014)

Abstract
This paper describes an existing database of geolocated tweets that were produced in Portuguese regions and proposes an approach to further expand it. The existing database covers eight consecutive days of collected tweets, totaling about 300 thousand tweets, produced by about 11 thousand different users. A detailed analysis on the content of the messages suggests a predominance of young authors that use Twitter as a way of reaching their colleagues with their feelings, ideas and comments. In order to further characterize this community of young people, we propose a method for retrieving additional tweets produced by the same set of authors already in the database. Our goal is to further extend the knowledge about each user of this community, making it possible to automatically characterize each user by the content he/she produces, cluster users and open other possibilities in the scope of social analysis.
Cite as

Gaspar Brogueira, Fernando Batista, João Paulo Carvalho, and Helena Moniz. Expanding a Database of Portuguese Tweets. In 3rd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 38, pp. 275-282, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{brogueira_et_al:OASIcs.SLATE.2014.275,
  author =	{Brogueira, Gaspar and Batista, Fernando and Carvalho, Jo\~{a}o Paulo and Moniz, Helena},
  title =	{{Expanding a Database of Portuguese Tweets}},
  booktitle =	{3rd Symposium on Languages, Applications and Technologies},
  pages =	{275--282},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-68-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{38},
  editor =	{Pereira, Maria Jo\~{a}o Varanda and Leal, Jos\'{e} Paulo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2014.275},
  URN =		{urn:nbn:de:0030-drops-45763},
  doi =		{10.4230/OASIcs.SLATE.2014.275},
  annote =	{Keywords: Twitter, corpus of Portuguese tweets, Twitter API, natural language processing, text analysis}
}
Document
DOI: 10.4230/OASIcs.SLATE.2014.283
MLT-prealigner: a Tool for Multilingual Text Alignment

Authors: Pedro Carvalho and José João Almeida

Published in: OASIcs, Volume 38, 3rd Symposium on Languages, Applications and Technologies (2014)

Abstract
Parallel text alignment is a key procedure in the automated translation area. A large number of aligners have been presented along the years, but these require that the target resources have been pre-prepared for alignment (either manually or automatically). It is rather normal to encounter mixed language documents, that is, documents where the same information is written in many languages (Ex: manuals of electronic devices, touristic information, PhD thesis with dual language abstracts, etc). In this article we present MLT-prealigner: a tool aimed at helping those that need to process mixed texts in order to feed alignment tools and other related language systems.
Cite as

Pedro Carvalho and José João Almeida. MLT-prealigner: a Tool for Multilingual Text Alignment. In 3rd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 38, pp. 283-290, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{carvalho_et_al:OASIcs.SLATE.2014.283,
  author =	{Carvalho, Pedro and Almeida, Jos\'{e} Jo\~{a}o},
  title =	{{MLT-prealigner: a Tool for Multilingual Text Alignment}},
  booktitle =	{3rd Symposium on Languages, Applications and Technologies},
  pages =	{283--290},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-68-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{38},
  editor =	{Pereira, Maria Jo\~{a}o Varanda and Leal, Jos\'{e} Paulo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2014.283},
  URN =		{urn:nbn:de:0030-drops-45776},
  doi =		{10.4230/OASIcs.SLATE.2014.283},
  annote =	{Keywords: parallel corpora, multilingual text alignment, language detection, Perl, automated translation}
}
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