Track: Quality Aspects of Empirical Studies
Throughout the years, empirical software engineering experienced an evergrowing research adoption trend. Bridging the gap between software engineering theory and industrial practice, empirical methods are nowadays widely utilized to understand and enhance the efficiency and effectiveness of software engineering processes. With the growing adoption of empirical methods for software engineering research, it becomes paramount not only to adopt sound empirical research methods but also to open the discourse on how we, as empirical software engineering researchers, can adapt, improve, optimize, and evaluate our investigation practices.
The QUATIC Quality Aspects of Empirical Studies (QAES) thematic track is designed to provide a forum to discuss the use of empirical methods in software engineering research. The thematic track welcomes submissions addressing all topics across the full spectrum of the quality of software engineering empirical studies, from practices aimed at improving current empirical software engineering research to discussing new avenues of empirical software engineering or the evaluation of empirical software engineering studies.
Among others, we invite submissions regarding topics related to:
Current practices in specific empirical software engineering research methods
Novel empirical software engineering research methods
Adaptations of renowned empirical methods to the software engineering context
Issues and considerations regarding empirical software engineering practices (e.g., sampling, threats to validity documentation)
Considerations regarding the application of empirical software engineering methods in industry
Lessons learned from applying empirical research methods to software engineering
Strategies and methods for evidence-based software engineering and secondary studies
Criteria and methods to evaluate the quality of empirical software engineering investigations
Reflections on current empirical software engineering trends
New and emerging trends in empirical software engineering research
Study design selection and mixed methods in empirical software engineering
Reproduction or replication of empirical studies with reflections on quality aspects and aggregated results
Roberto Verdecchia is an Assistant Professor at the Software Technologies Laboratory (STLab) of the University of Florence, Italy. He holds a double Ph.D. in Computer Science, appointed by the Gran Sasso Science Institute, L’Aquila, Italy, and the Vrije Universiteit Amsterdam, the Netherlands. His research interests focus on the adoption of empirical methods to improve software development and system evolution, with particular interest in the fields of technical debt, software architecture, software energy efficiency, and software testing. More information is available at robertoverdecchia.github.io.
Marcos Kalinowski is a software engineering professor at PUC-Rio, Brazil. His research focuses on empirical software engineering, human aspects, requirements engineering, software quality, and the intersection between software engineering and data science. He is a member of the International Software Engineering Research Network (ISERN). Before becoming a professor, he spent over ten years in the software industry. His research has an in-depth focus on the problems and needs of the software industry, received several honors and awards, and is available in publications in some of the main software engineering journals and conferences. He serves the community as editor of the Journal of Systems and Software’s In-Practice track and as part of several international conferences' organizing and program committees.