Track: Software Quality Education and Training in Academia and Industry
ABOUT
Currently, the nature of software is changing and so is its quality. Wth the advent of new technologies, different types of software applications (mobile applications, ubiquitous, embedded, for IoT, smart applications, and so on) have emerged and supported the different activities of daily life. To make those applications accepted and really useful, we have to guarantee their quality. To that end, the quality community has sought to integrate training on techniques, methods, and methods in the undergraduate and graduate course curricula (sometimes integrated dispersed in several disciplines) and sought to bring specific interest training to the industry (for example, to obtain quality certifications for specific models/standards, training in testing and others).
This track is looking for contributions on:
Experience papers on software quality education presenting original reports on how software quality has been integrated into undergraduate and graduate programs.
Experience papers on software quality education presenting original reports on how software quality subjects have been transferred to the industry
Research papers describing original and scientifically rigorous contributions concerning to challenges, innovations, and best practices in software quality education and training in academia and industry.
TOPICS
We are open to a wide range of topics, including (but not limited to):
new and innovative best practices for software quality education and training;
innovative curriculum or course formats;
software quality education to the masses (i.e., MOOCs);
teaching software quality in non-traditional contexts such as mobile and web applications, ubiquitous and IoT applications, low-code and no-code development in academia and industry;
emerging educational settings for software quality such as online learning;
cooperation in software quality education between industry and academia;
methodological aspects of software quality education;
use of machine learning approaches for collecting data to assure the software quality in academia and industry;
teaching of processes, methods, techniques, and tools for software quality and testing;
problem-based/project based teaching/learning in software quality.
TRACK COMMITTEE
Chair: Káthia Marçal de Oliveira, Polytechinic University of Hauts-de-France, France
Program Committee:
Ana Regina Rocha, Federal University of Rio de Janeiro, Brazil
Christophe Kolski, Université Polytechnique Hauts-de-France, France
Claudia Werner, Federal University of Rio de Janeiro, Brazil
Daniel Fernández Lanvin, University of Oviedo, Spain
Eduardo Figueiredo, Federal University of Minas Gerais, Brazil
Emily Oh Navarro, University of California, USA
Hieke Keuning, Utrecht University
Jaejoon Lee, University of East Anglia, UK
Lerina Aversano, Università degli Studi del Sannio, Italy
Luigia Petre, Åbo Akademi University, Finland
Luis Olsina, National Unviersity of La Pampa, Argentina
Martin Gonzalez-Rodriguez, University of Oviedo, Spain
Moisés Rodríguez, AQCLab & Universidad de Castilla-La Mancha, Spain
Pierre-Emmanuel Arduin, Paris-Dauphine Unviersity, France
Rafael Capilla, University Rey Juan Carlos, Spain
Rafael Duque, University of Cantabria, Spain
Samira Cherfi, Conservatoire National des Arts et Métiers, France
Sheila Reinehr, Pontifical Catholic University of Parana, Brazil
Sybille Caffiau, Université Grenoble Alpes, France
Toacy Oliveira, Federal University of Rio de Janeiro, Brazil
Káthia Marçal de Oliveira is professor at the department of Computer Science of Polytechinic University of Hauts-de-France. She received her Ph.D. degree from the Graduate School of Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil in 1999. She has experience in software quality evaluation and Human-Computer Interaction evaluation. She has been working on software quality education and training since 1999, both in undergraduate and graduate courses, and also in industry.