67 Search Results for "Queirós, Ricardo"

Volume

OASIcs, Volume 133

6th International Computer Programming Education Conference (ICPEC 2025)

ICPEC 2025, July 10-11, 2025, PORTIC, Polytechnic of Porto, Portugal

Editors: Ricardo Queirós, Mário Pinto, Filipe Portela, and Alberto Simões

Volume

OASIcs, Volume 112

4th International Computer Programming Education Conference (ICPEC 2023)

ICPEC 2023, June 26-28, 2023, Vila do Conde, Portugal

Editors: Ricardo Alexandre Peixoto de Queirós and Mário Paulo Teixeira Pinto

Volume

OASIcs, Volume 94

10th Symposium on Languages, Applications and Technologies (SLATE 2021)

SLATE 2021, July 1-2, 2021, Vila do Conde/Póvoa de Varzim, Portugal

Editors: Ricardo Queirós, Mário Pinto, Alberto Simões, Filipe Portela, and Maria João Pereira

Volume

OASIcs, Volume 91

Second International Computer Programming Education Conference (ICPEC 2021)

ICPEC 2021, May 27-28, 2021, University of Minho, Braga, Portugal

Editors: Pedro Rangel Henriques, Filipe Portela, Ricardo Queirós, and Alberto Simões

Volume

OASIcs, Volume 83

9th Symposium on Languages, Applications and Technologies (SLATE 2020)

SLATE 2020, July 13-14, 2020, School of Technology, Polytechnic Institute of Cávado and Ave, Portugal (Virtual Conference)

Editors: Alberto Simões, Pedro Rangel Henriques, and Ricardo Queirós

Volume

OASIcs, Volume 81

First International Computer Programming Education Conference (ICPEC 2020)

ICPEC 2020, June 25-26, 2020, ESMAD, Vila do Conde, Portugal (Virtual Conference)

Editors: Ricardo Queirós, Filipe Portela, Mário Pinto, and Alberto Simões

Volume

OASIcs, Volume 56

6th Symposium on Languages, Applications and Technologies (SLATE 2017)

SLATE 2017, June 26-27, 2017, Vila do Conde, Portugal

Editors: Ricardo Queirós, Mário Pinto, Alberto Simões, José Paulo Leal, and Maria João Varanda

Volume

OASIcs, Volume 21

1st Symposium on Languages, Applications and Technologies

SLATE 2012, June 21-22, 2012, Braga, Portugal

Editors: Alberto Simões, Ricardo Queirós, and Daniela da Cruz

Document
Complete Volume
DOI: 10.4230/OASIcs.ICPEC.2025
OASIcs, Volume 133, ICPEC 2025, Complete Volume

Authors: Ricardo Queirós, Mário Pinto, Filipe Portela, and Alberto Simões

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

Abstract
OASIcs, Volume 133, ICPEC 2025, Complete Volume
Cite as

6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 1-226, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Proceedings{queiros_et_al:OASIcs.ICPEC.2025,
  title =	{{OASIcs, Volume 133, ICPEC 2025, Complete Volume}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{1--226},
  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},
  URN =		{urn:nbn:de:0030-drops-245929},
  doi =		{10.4230/OASIcs.ICPEC.2025},
  annote =	{Keywords: OASIcs, Volume 133, ICPEC 2025, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/OASIcs.ICPEC.2025.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Ricardo Queirós, Mário Pinto, Filipe Portela, and Alberto Simões

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

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 0:i-0:xii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{queiros_et_al:OASIcs.ICPEC.2025.0,
  author =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{0:i--0:xii},
  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.2025.0},
  URN =		{urn:nbn:de:0030-drops-245910},
  doi =		{10.4230/OASIcs.ICPEC.2025.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
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
DOI: 10.4230/OASIcs.ICPEC.2025.1
Exploring Mutation Testing for Teaching Introductory Programming

Authors: Pedro Vasconcelos

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

Abstract
This paper proposes the use of introductory programming assignments based on mutation testing where students are asked to write tests rather than code. We believe such exercises can be used to teach code reading skills before students could write the corresponding programs on their own. Furthermore, feedback for such exercises can be automatically generated using testing tools. We have extended an existing web-based system for programming exercises with such mutation testing assignments and show some example use cases. This is on-going work that has yet to be validated in the classroom.
Cite as

Pedro Vasconcelos. Exploring Mutation Testing for Teaching Introductory Programming. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 1:1-1:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{vasconcelos:OASIcs.ICPEC.2025.1,
  author =	{Vasconcelos, Pedro},
  title =	{{Exploring Mutation Testing for Teaching Introductory Programming}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{1:1--1:8},
  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.2025.1},
  URN =		{urn:nbn:de:0030-drops-240319},
  doi =		{10.4230/OASIcs.ICPEC.2025.1},
  annote =	{Keywords: mutation testing, programming education}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2025.17
Osiris: A Multi-Language Transpiler for Educational Purposes

Authors: Breno Marrão, José Paulo Leal, and Ricardo Queirós

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

Abstract
While server-side assessment of programming exercises, with its ease of installing diverse compilers and execution environments, is common, it presents three key limitations: the necessity of a constant Internet connection, increased bandwidth consumption, and centralized execution load. The alternative is to rely on JavaScript, the single programming language supported by all standard web browsers. This paper introduces Osiris, a pure JavaScript multi-language transpiler designed to enable the execution of diverse programming languages within web browsers. Targeted primarily at Virtual Learning Environments (VLE) for language programming education, Osiris employs a parser generator to translate small student programs into JavaScript based on language-specific grammars with semantic rules. It also includes a comprehensive, though not exhaustive, JavaScript library that emulates the standard libraries of its supported languages. Validation of Osiris indicates the pedagogical effectiveness of browser-based transpilation for introductory programming education.
Cite as

Breno Marrão, José Paulo Leal, and Ricardo Queirós. Osiris: A Multi-Language Transpiler for Educational Purposes. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{marrao_et_al:OASIcs.ICPEC.2025.17,
  author =	{Marr\~{a}o, Breno and Leal, Jos\'{e} Paulo and Queir\'{o}s, Ricardo},
  title =	{{Osiris: A Multi-Language Transpiler for Educational Purposes}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{17:1--17:14},
  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.2025.17},
  URN =		{urn:nbn:de:0030-drops-240471},
  doi =		{10.4230/OASIcs.ICPEC.2025.17},
  annote =	{Keywords: Transpiler, Programming Education, JavaScript, Python, Virtual Learning Environments, Client-Side Execution}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2025.4
Can Open Large Language Models Catch Vulnerabilities?

Authors: Diogo Gaspar Lopes, Tiago Espinha Gasiba, Sathwik Amburi, and Maria Pinto-Albuquerque

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

Abstract
As Large Language Models (LLMs) become increasingly integrated into secure software development workflows, a critical question remains unanswered: can these models not only detect insecure code but also reliably classify vulnerabilities according to standardized taxonomies? In this work, we conduct a systematic evaluation of three state-of-the-art LLMs - Llama3, Codestral, and Deepseek R1 - using a carefully filtered subset of the Big-Vul dataset annotated with eight representative Common Weakness Enumeration categories. Adopting a closed-world classification setup, we assess each model’s performance in both identifying the presence of vulnerabilities and mapping them to the correct CWE label. Our findings reveal a sharp contrast between high detection rates and markedly poor classification accuracy, with frequent overgeneralization and misclassification. Moreover, we analyze model-specific biases and common failure modes, shedding light on the limitations of current LLMs in performing fine-grained security reasoning.These insights are especially relevant in educational contexts, where LLMs are being adopted as learning aids despite their limitations. A nuanced understanding of their behaviour is essential to prevent the propagation of misconceptions among students. Our results expose key challenges that must be addressed before LLMs can be reliably deployed in security-sensitive environments.
Cite as

Diogo Gaspar Lopes, Tiago Espinha Gasiba, Sathwik Amburi, and Maria Pinto-Albuquerque. Can Open Large Language Models Catch Vulnerabilities?. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 4:1-4:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gasparlopes_et_al:OASIcs.ICPEC.2025.4,
  author =	{Gaspar Lopes, Diogo and Espinha Gasiba, Tiago and Amburi, Sathwik and Pinto-Albuquerque, Maria},
  title =	{{Can Open Large Language Models Catch Vulnerabilities?}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{4:1--4:14},
  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.2025.4},
  URN =		{urn:nbn:de:0030-drops-240340},
  doi =		{10.4230/OASIcs.ICPEC.2025.4},
  annote =	{Keywords: Large Language Models (LLMs), Secure Coding, CWE Classification, Machine Learning, Software Vulnerability Detection, Artificial Intelligence, Code Analysis, Big-Vul Dataset}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2025.15
Designing a Multi-Narrative Gamified Learning Experience

Authors: Yannik Bauer, José Paulo Leal, Ricardo Queirós, Jakub Swacha, and José Paiva

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

Abstract
The combination of storytelling and gamification in educational settings has emerged as a method to enhance student engagement and learning outcomes. Through an overarching narrative, course content can be connected while providing context for gamified exercises, creating a motivating and competitive learning experience. However, a narrative that resonates with one student may not interest others. The presented solution to this problem is to offer multiple narratives for students to choose from. This enables the students to engage with the material in ways that align with their interests and motivations. Yet, managing multiple narratives presents several challenges. Each narrative must cover all syllabus topics equally, and every exercise must be available across all narratives while maintaining consistent difficulty levels and learning objectives. This paper presents a systematic approach for creating gamified courses with multiple narratives. The methodology includes the development of a base course template and its narrative variations, along with transformation processes to generate exercises in the FGPE Ecosystem, namely AuthorKit and FGPE PLE. The final output is a single Moodle MBZ file that can be imported into Moodle, a widely adopted learning management system.
Cite as

Yannik Bauer, José Paulo Leal, Ricardo Queirós, Jakub Swacha, and José Paiva. Designing a Multi-Narrative Gamified Learning Experience. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 15:1-15:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bauer_et_al:OASIcs.ICPEC.2025.15,
  author =	{Bauer, Yannik and Leal, Jos\'{e} Paulo and Queir\'{o}s, Ricardo and Swacha, Jakub and Paiva, Jos\'{e}},
  title =	{{Designing a Multi-Narrative Gamified Learning Experience}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{15:1--15:8},
  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.2025.15},
  URN =		{urn:nbn:de:0030-drops-240450},
  doi =		{10.4230/OASIcs.ICPEC.2025.15},
  annote =	{Keywords: Gamification, Storytelling, Personalized Learning, Programming Education, Multi-Narrative}
}
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