Accepted Papers


An Experience Report on Modeling Software Process in Industrial Context: Challenges and Solutions

By: Yue Li, He Zhang, Liming Dong, Bohan Liu and Lanxin Yang

Breaking old Habits: On Success Factors in Software Process Improvement

By: Kseniia Vasylieva, Steffen Küpper and Marco Kuhrmann

Capability Modeling for Corporate Cognition

By: Stanley Sutton Jr.

Fully Automated DORA Metrics Measurement for Continuous Improvement

By: Janick Rüegger, Martin Kropp, Sebastian Graf and Craig Anslow

Insights on Implementing a Metrics Baseline for Post-Deployment AI Container Monitoring

By: Dr. Jose Andre Morales, Luiz Antunes, Patrick Earl, Dr. Robert Edman, Jeff Hamed, Douglas Reynolds, Katherine R. Maffey, Joseph Yankel and Hasan Yasar

Interaction Prediction and Anomaly Detection in a Microservices-based Telecommunication Platform

By: Kemal Aktaş and H. Hakan Kilinc

Maintaining security consistency during system development with security-oriented model federation

By: Chahrazed Boudjemila, Fabien Dagnat and Salvador Martínez

Software Process as a Service: Towards A Software Process Ecosystem

By: Oliver Greulich, Christoph Knieke, Bassel Rafie, Andreas Rausch and Marco Kuhrmann

Supporting Engineering Process Compliance via Generation of Detailed Guidance Actions

By: Anmol Bilal, Christoph Mayr-Dorn and Alexander Egyed


Coming shortly!


EuroSPI Conference 2024 and ICSSP 2024 Joint Keynote Panel Session

Harnessing the Potential of Generative AI for Software Systems Development

September 4, 2024
, 4:00 pm
–5:30 pm
 / 2:00 pm
–3:30 pm UTC
In-person and virtual/online

We stand at a pivotal moment in software engineering, with AI-driven approaches poised to enhance the development, testing, and sustainment of software. While Generative AI tools initially sparked excitement for their potential to reduce errors, scale changes effortlessly, and drive innovation, concerns have emerged. These concerns encompass security risks, unforeseen failures, and issues of trust. Empirical research on Generative AI development assistants reveals that productivity and quality gains hinge not solely on tool sophistication but also on task flow redesign and expert judgment. Drawing insights from the study “Architecting the Future of Software Engineering: A National Agenda for Software Engineering R&D” we will focus on the critical technologies and research areas essential for advancing future systems, with the overarching goal of making software a competitive advantage.

Our keynote panel will explore the future of software engineering using Generative AI technologies from multiple perspectives. We’ll examine current applications, envision future possibilities, identify research gaps, and identify critical skill sets required by software engineers and stakeholders to harness Generative AI’s potential effectively and responsibly. By fostering a deeper understanding of AI’s role in software engineering, we aim to accentuate its potential and mitigate its risks.

Panel Chair:

Anita Carleton, Carnegie Mellon University, Software Engineering Institute Executive Software Solutions Director, IEEE Fellow


Professor Lionel Briand, Science Foundation Ireland Research Centre for Software, Director

Dr. Ipek Ozkaya, Carnegie Mellon University Software Engineering Institute Engineering Intelligent Software Systems Technical Director

Dr. Alexander Poth, Volkswagen Audi Group

John Robert, Carnegie Mellon University Software Engineering Institute Software Solutions Deputy Director

Thomas Kropf, President Bosch Corporate Research and Advance Engineering


Coming shortly!