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Sobre

Sobre

Ana Paiva (publica como Ana C. R. Paiva) é Professora Auxiliar no Departamento de Engenharia Informática da Faculdade de Engenharia da Universidade do Porto, onde trabalha desde 1999. Ela é investigadora no INESC TEC na área de Engenharia de Software e membro do Grupo de Engenharia de Software que reúne investigadores e pós-graduados com interesses comuns em Engenharia de Software. É responsável por unidades curriculares como Teste de Software, Métodos Formais e Engenharia de Software, entre outras. Tem um doutoramento em Engenharia Electrotécnica e Computadores da FEUP, com uma tese intitulada Automated Specification Based Testing of Graphical User Interfaces. A sua especialidade é a implementação e automação do processo de teste baseado em modelos. Desenvolveu trabalho de investigação em colaboração com o grupo FSE (Foundation of Software Engineering) da Microsoft Research, onde teve a oportunidade de estender a ferramenta de testes da Microsoft baseada em modelo, Spec Explorer, para o teste de GUIs. É a investigadora responsável de um projeto financiado pela FCT com o tema Pattern-Based Testing GUI (PBGT). Pertence à Assemblia Geral da PSTQB (Associação Portuguesa de Testes de Software), é membro dos grupos internacionais de trabalho do ISTQB: TBok, Glossary, MBT Examination, membro do Conselho do Departamento de Engenharia Informática, e membro da Comissão Executiva do Departamento de Engenharia Informática.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Ana Cristina Paiva
  • Cargo

    Investigador Sénior
  • Desde

    01 fevereiro 2014
002
Publicações

2023

Collecting cognitive strategies applied by students during test case design

Autores
Cammaerts, F; Snoeck, M; Paiva, ACR;

Publicação
27TH INTERNATIONAL CONFERENCE ON EVALUATION AND ASSESSMENT IN SOFTWARE ENGINEERING, EASE 2023

Abstract
It is important to properly test developed software because this may contribute to fewer bugs going unreported in deployed software. Often, little attention is spent on the topic of software testing in curricula, yielding graduate students without adequate preparation to deal with the quality standards required by the industry. This problem could be tackled by introducing bite-sized software testing education capsules that allow teachers to introduce software testing to their students in a less time-consuming manner and with a hands-on component that will facilitate learning. In order to design appropriate software testing educational tools, it is necessary to consider both the software testing needs of the industry and the cognitive models of students. This work-in-progress paper proposes an experimental design to gain an understanding of the cognitive strategies used by students during test case design based on real-life cases. Ultimately, the results of the experiment will be used to develop educational support for teaching software testing.

2023

ENACTEST project - European Innovation Alliance for Testing Education

Autores
Marín, B; Vos, TEJ; Snoeck, M; Paiva, ACR; Fasolino, AR;

Publicação
Proceedings of the Research Projects Exhibition Papers Presented at the 35th International Conference on Advanced Information Systems Engineering (CAiSE 2023), Zaragoza, Spain, June 12-16, 2023.

Abstract

2023

An Approach to Regression Testing Selection based on Code Changes and Smells

Autores
Mori, A; Paiva, ACR; Souza, SRS;

Publicação
PROCEEDINGS OF THE 8TH BRAZILIAN SYMPOSIUM ON SYSTEMATIC AND AUTOMATED SOFT-WARE TESTING, SAST 2023

Abstract
Regression testing is a software engineering maintenance activity that involves re-executing test cases on a modified software system to check whether code changes introduce new faults. However, it can be time-consuming and resource-intensive, especially for large systems. Regression testing selection techniques can help address this issue by selecting a subset of test cases to run. The change-based technique selects a subset of test cases based on the modified software classes, reducing the test suite size. Thereby, it will cover a smaller number of classes, decreasing the efficiency of the test suite to reveal design flaws. From this perspective, code smells are known to identify poor design and threaten the quality of software systems. In this study, we propose an approach to combine code change and smell to select regression tests and present two new techniques: code smell based and code change and smell. Additionally, we developed the Regression Testing Selection Tool (RTST) to automate the selection process. We empirically evaluated the approach in Defects4J projects by comparing the new techniques' effectiveness with the change-based as a baseline. The results show that the change-based technique achieves the highest reduction rate in the test suite size but with less class coverage. On the other hand, test cases selected using code smells and changed classes combined can potentially find more bugs. The code smell-based technique provides a comparable class coverage to the code change and smell approach. Our findings highlight the benefits of incorporating code smells in regression testing selection and suggest opportunities for improving the efficiency and effectiveness of regression testing.

2022

ENACTEST - European Innovation Alliance for Testing Education

Autores
Marín, B; Vos, TEJ; Paiva, ACR; Fasolino, AR; Snoeck, M;

Publicação
Joint Proceedings of RCIS 2022 Workshops and Research Projects Track co-located with the 16th International Conference on Research Challenges in Information Science (RCIS 2022), Barcelona, Spain, May 17-20, 2022.

Abstract
Testing software is very important, but not done well, resulting in problematic and erroneous software applications. The cause radicates from a skills mismatch between what is needed in industry, the learning needs of students, and the way testing is currently being taught at higher and vocational education institutes. The goal of this project is to identify and design seamless teaching materials for testing that are aligned with industry and learning needs. To represent the entire socio-economic environment that will benefit from the results, this project consortium is composed of a diverse set of partners ranging from universities to small enterprises. The project starts with research in sensemaking and cognitive models when doing and learning testing. Moreover, a study will be done to identify the needs of industry for training and knowledge transfer processes for testing. Based on the outcomes of this research and the study, we will design and develop capsules on teaching software testing including the instructional materials that take into account the cognitive models of students and the industry needs. Finally, we will validate these teaching testing capsules developed during the project. © 2021 The Authors.

2022

Towards the Art of Writing Agile Requirements with User Stories, Acceptance Criteria, and Related Constructs

Autores
Ferreira, AMS; da Silva, AR; Paiva, ACR;

Publicação
ENASE: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING

Abstract
Nowadays, more organizations adopt agile methodologies to guarantee short and frequent delivery times. A plethora of novel approaches and concepts regarding requirements engineering in this context are emerging. User stories are usually informally described as general explanations of software features, written from end-users perspective, while acceptance criteria are high-level conditions that enable their verification. This paper focuses on the art of writing user stories and acceptance criteria, but also on their relationships with other related concepts, such as quality requirements. In the pursuance of deriving guidelines and linguistic patterns to facilitate the writing of requirements specifications, a systematic literature review was conducted to provide a cohesive and comprehensive analysis of such concepts. Despite considerable research on the subject, no formalized model and systematic approach to assist this writing. We provide a coherent analysis of these concepts and related linguistic patterns supported by a running example of specifications built on top of ITLingo RSL, a publicly available tool to enforce the rigorous writing of specification artefacts. We consider that adopting and using the guidelines and patterns from the present discussion contribute to writing better and more consistent requirements.

Teses
supervisionadas

2022

Towards a Privacy-Preserving Distributed Machine Learning Framework

Autor
Cláudia Vanessa Martins de Brito

Instituição
UM

2022

Analysis and Implementation of White-Box Crypto AES in JavaScript

Autor
Simão Pereira de Oliveira

Instituição
UP-FEUP

2021

Gestão de Frota - Visão 360º

Autor
Pedro Manuel Almeida Roseira

Instituição
UP-FEUP

2021

Willingness to pay for green premiums through a sustainable marketplace

Autor
Francisco Armando Teixeira Ferreira

Instituição
UP-FEUP

2021

Análise e Classificação por Aprendizagem Máquina do Doente Neurocrítico

Autor
Cârmen Isabel Ribeiro Vieira

Instituição
UNL-FCTNOVA