IDoESE Doctoral SymposiumESEIW 2024
International Doctoral Symposium on Empirical Software Engineering – IDoESE 2024
Empirical research is the backbone of most sciences and is of growing importance in software engineering. The Empirical Software Engineering community has significantly advanced the state of the art in this area. Researchers now apply a variety of empirical techniques, but choosing the correct methods and applying them to answer interesting research questions is still an art.
The objective of the doctoral symposium is to provide early- and mid-stage PhD students with a forum to discuss their work, ask questions of senior researchers, and receive constructive feedback on their PhD topics and research plans. Accepted papers will be published in post-conference proceedings.
The core of the symposium are presentations by PhD students to a panel of senior faculty and research scientists, who will provide ideas, questions, and other feedback to the students.
Participation
The symposium is targeted at PhD students in the early- and mid- stages of their PhD. At a minimum, participants must have selected a PhD topic, identified a set of research questions, and have at least a preliminary research design. The symposium is not appropriate for PhD students at the end of their PhD who have completed all their research activities.
Students’ PhD topics must have an empirical focus that is a critical part of the research plan. The PhD topic must be a software engineering topic, such as software process, requirements, design, coding practice, verification methods, software security engineering, software metrics, human factors in software development, and empirical research methods for software engineering.
Submission instructions
Students must submit:
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A research proposal describing their PhD topic, research questions, research plan, and results to date, if any. The recommended length is four pages, but we allow up to six pages in case there are a lot of results or large mandatory figures for example. A brief letter of recommendation should be provided by the supervisor to verify the student’s status.
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The submission must be written in English, should be submitted via EasyChair in the PDF format, and must be formatted according to the ACM proceedings template, which can be found at ACM Proceedings Template. Please use the sigconf-option to get it correctly formatted in two-columns. Both documents, the proposal and the recommendation letter, should be submitted via EasyChair.
Symposium presentation
An Expert Panel will evaluate all submissions. The students, that submitted accepted proposals, will be invited to present their proposal at the Doctoral Symposium. Participants must attend the symposium on October 23th, 2024 and prepare a presentation on the contents of their paper. During the presentation, the Expert Panel will ask the students questions and offer feedback.
Note: It is important to notice that the person that will present an accepted paper must be the doctoral student, the author of the paper. Professors and colleagues are not allowed to present papers on behalf of the doctoral student. Furthermore, advisors should not attend their students’ sessions.
Important Dates
(All dates are end of day, anywhere on earth)
Submission: June 26, 2024
Notification: July 26, 2024
Camera-ready: September 6, 2024
Doctoral symposium: October 23, 2024
Expert Panel
Claudia Ayala, Universitat Politècnica de Cataluna, Spain
Marcela Genero, Universidad de Castilla-La Mancha, Spain
Valentina Lenarduzzi, University of Oulu, Finland
Sira Vegas, Universitad Politécnica de Madrid, Spain
Stefan Wagner, Technical University of Munich, Germany
Wed 23 OctDisplayed time zone: Brussels, Copenhagen, Madrid, Paris change
08:45 - 10:30 | |||
08:45 15mDay opening | Introductions IDoESE Doctoral Symposium D: Silvia Abrahão Universitat Politècnica de València, D: Daniela Cruzes Norwegian University of Science and Technology | ||
09:00 60mKeynote | Peer Reviewing in Empirical Software Engineering: The Good, the Bad, and the Ugly IDoESE Doctoral Symposium File Attached | ||
10:00 30mDoctoral symposium paper | Effective and Efficient Scenarios for Simulation-Based Safety Testing of Automated Driving Systems IDoESE Doctoral Symposium A: Fauzia Khan University of Tartu, Estonia, M: Valentina Lenarduzzi University of Oulu, M: Stefan Wagner Technical University of Munich |
10:30 - 11:00 | |||
10:30 30mCoffee break | Break Catering |
11:00 - 12:30 | |||
11:00 30mDoctoral symposium paper | Towards Developing a Comprehensive Methodical Framework for Evaluating Code Recommender Systems IDoESE Doctoral Symposium A: Daniel Borst Vienna University of Economics and Business, Institute for Complex Networks, M: Valentina Lenarduzzi University of Oulu, M: Sira Vegas Universidad Politecnica de Madrid | ||
11:30 30mDoctoral symposium paper | Understanding and Eliminating Barriers to Replications in Behavioural Software Engineering IDoESE Doctoral Symposium A: Florian Poreba Vienna University of Economics and Business, M: Valentina Lenarduzzi University of Oulu, M: Sira Vegas Universidad Politecnica de Madrid, M: Stefan Wagner Technical University of Munich | ||
12:00 30mDoctoral symposium paper | Dealing with Time Dependence in Empirical Software Engineering IDoESE Doctoral Symposium A: Mikel Robredo University of Oulu, M: Sira Vegas Universidad Politecnica de Madrid, M: Stefan Wagner Technical University of Munich |
12:30 - 14:00 | |||
12:30 90mLunch | Lunch Catering |
14:00 - 15:30 | |||
14:00 30mDoctoral symposium paper | Improving Software Modeling through gamification and automated agents IDoESE Doctoral Symposium A: Giacomo Garaccione Politecnico di Torino, M: Marcela Fabiana Genero Bocco University of Castilla-La Mancha, M: Valentina Lenarduzzi University of Oulu | ||
14:30 30mDoctoral symposium paper | Responsible development and use of AI: a metric-based framework for enabling empirical evaluations IDoESE Doctoral Symposium A: Marco Rondina Politecnico di Torino, M: Claudia Ayala Universitat Politècnica de Catalunya, Spain, M: Marcela Fabiana Genero Bocco University of Castilla-La Mancha, M: Valentina Lenarduzzi University of Oulu | ||
15:00 30mDoctoral symposium paper | Research proposal: An Analysis an Model of Positionality Statements in Software Engineering Research IDoESE Doctoral Symposium A: Breno Felix de Sousa Federal University of Pernambuco, M: Claudia Ayala Universitat Politècnica de Catalunya, Spain, M: Valentina Lenarduzzi University of Oulu |
15:30 - 16:00 | |||
15:30 30mCoffee break | Break Catering |
16:00 - 17:30 | |||
16:00 30mDoctoral symposium paper | Analysing Dependency Issues of Workflows in the GitHub Actions Ecosystem IDoESE Doctoral Symposium A: Hassan Onsori Delicheh University of Mons, Belgium, M: Claudia Ayala Universitat Politècnica de Catalunya, Spain, M: Valentina Lenarduzzi University of Oulu | ||
16:30 60mPanel | Do's and Don'ts When Performing Doctoral Studies IDoESE Doctoral Symposium P: Claudia Ayala Universitat Politècnica de Catalunya, Spain, P: Valentina Lenarduzzi University of Oulu, D: Silvia Abrahão Universitat Politècnica de València, D: Daniela Cruzes Norwegian University of Science and Technology |
Accepted Papers
Title | |
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Analysing Dependency Issues of Workflows in the GitHub Actions Ecosystem IDoESE Doctoral Symposium | |
Dealing with Time Dependence in Empirical Software Engineering IDoESE Doctoral Symposium | |
Effective and Efficient Scenarios for Simulation-Based Safety Testing of Automated Driving Systems IDoESE Doctoral Symposium | |
Improving Software Modeling through gamification and automated agents IDoESE Doctoral Symposium | |
Research proposal: An Analysis an Model of Positionality Statements in Software Engineering Research IDoESE Doctoral Symposium | |
Responsible development and use of AI: a metric-based framework for enabling empirical evaluations IDoESE Doctoral Symposium | |
Towards Developing a Comprehensive Methodical Framework for Evaluating Code Recommender Systems IDoESE Doctoral Symposium | |
Understanding and Eliminating Barriers to Replications in Behavioural Software Engineering IDoESE Doctoral Symposium |