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About

About

João Pascoal Faria holds a PhD in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto in 1999, where he is currently Associate Professor at the Department of Informatics Engineering and Director of the Integrated Master in Informatics and Computing Engineering (MIEIC). He his a member of the Software Engineering Research Group (softeng.fe.up.pt) and researcher at INESC TEC, where he coordinates the Software Engineering area. He represents FEUP and INESC TEC in the Technical Comission for Health Informatics (CT 199) and FEUP as President of the Sectorial Comission for the Quality of Information and Communications Technology (CS/03), in the scope of the Portuguese Quality Institute (IPQ). In the past, he worked with several software companies (Novabase Saúde, Sidereus, Medidata) and was a co-founder of two other (Qualisoft and Strongstep). He has more than 25 years of experience in education, research, development and consultancy in several software engineering areas. He is the main author of a rapid application development tool (SAGA), based on domain specific languages, with more than 25 years of market presence and evolution (1989-present). He is currently involved in research projects, supervisions and consulting activities in the areas of model-based testing, software process improvement and model-driven development.

Interest
Topics
Details

Details

  • Name

    João Pascoal Faria
  • Cluster

    Computer Science
  • Role

    Area Manager
  • Since

    14th October 1985
002
Publications

2019

Automatic calibration of performance indicators for performance analysis in software development

Authors
Raza, M; Faria, JP;

Publication
Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE

Abstract
ProcessPAIR is a novel method and tool for automating the performance analysis in software development. Based on performance models structured by process experts and calibrated from the performance data of many developers, it automatically identifies and ranks potential performance problems and root causes of individual developers. However, the current calibration method is not fully automatic, because, in the case of performance indicators that affect other indicators in a conflicting way, the process expert has to manually calibrate the optimal value in a way that balances those impacts. In this paper we propose a novel method to automate this step, taking advantage of training data sets. We demonstrate the feasibility of the method with an example related with the Code Review Rate indicator, with conflicting impacts on Productivity and Quality.

2019

Message from the a- Most 2019 chairs

Authors
Hierons, R; Núñez, M; Pretschner, A; Gargantini, A; Faria, JP; Wang, S;

Publication
Proceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019

Abstract

2019

Assisting software engineering students in analyzing their performance in software development

Authors
Raza, M; Faria, JP; Salazar, R;

Publication
Software Quality Journal

Abstract
Collecting product and process measures in software development projects, particularly in education and training environments, is important as a basis for assessing current performance and opportunities for improvement. However, analyzing the collected data manually is challenging because of the expertise required, the lack of benchmarks for comparison, the amount of data to analyze, and the time required to do the analysis. ProcessPAIR is a novel tool for automated performance analysis and improvement recommendation; based on a performance model calibrated from the performance data of many developers, it automatically identifies and ranks potential performance problems and root causes of individual developers. In education and training environments, it increases students’ autonomy and reduces instructors’ effort in grading and feedback. In this article, we present the results of a controlled experiment involving 61 software engineering master students, half of whom used ProcessPAIR in a Personal Software Process (PSP) performance analysis assignment, and the other half used a traditional PSP support tool (Process Dashboard) for performing the same assignment. The results show significant benefits in terms of students’ satisfaction (average score of 4.78 in a 1–5 scale for ProcessPAIR users, against 3.81 for Process Dashboard users), quality of the analysis outcomes (average grades achieved of 88.1 in a 0–100 scale for ProcessPAIR users, against 82.5 for Process Dashboard users), and time required to do the analysis (average of 252 min for ProcessPAIR users, against 262 min for Process Dashboard users, but with much room for improvement). © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

2018

Automatic Model Transformation from UML Sequence Diagrams to Coloured Petri Nets

Authors
Custódio Soares, JA; Lima, B; Faria, JP;

Publication
Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2018, Funchal, Madeira - Portugal, January 22-24, 2018.

Abstract

2018

End-to-end Automatic Business Process Validation

Authors
Paiva, ACR; Flores, NH; Faria, JP; Marques, JMG;

Publication
Procedia Computer Science

Abstract

Supervised
thesis

2017

Workflow engine for parallel batch processing

Author
João Guilherme Rodrigues Marques de Oliveira

Institution
UP-FEUP

2017

Automated Scenario-based Testing of Distributed and Heterogeneous Systems

Author
Bruno Miguel Carvalhido Lima

Institution
UP-FEUP

2017

Atribuição automática de estudantes universitários a turmas baseada em otimização multicritério

Author
Gustavo Teixeira Nunes da Silva

Institution
UP-FEUP

2017

Sistema de acompanhamento curricular

Author
Jorge Filipe Vieira Barbosa Teixeira

Institution
UP-FEUP

2017

Avaliação Automática de Programas em Contexto de E-learning

Author
José Alberto de Carvalho Cardoso

Institution
UP-FEUP