Opening & KeynotesVARIABILITY 2026

Jean-Marc Jézéquel

Biography:
Jean-Marc Jézéquel is a Professor of Software Engineering at the University of Rennes and a member of the DiverSE team at IRISA/Inria, as well as a fellow of the Institut Universitaire de France (IUF) and a Senior Member of the IEEE. Since 2024, he is President of Informatics Europe. From 2012 to 2020, he was Director of IRISA, one of the largest public research labs in Informatics in France. In 2016 he received the Silver Medal from CNRS and in 2020 the IEEE/ACM MODELS career award. He was an invited professor at McGill University in 2022. His interests include model-driven software engineering, software product lines, and digital twins. He is the author of 4 books and of more than 300 publications in international journals and conferences. He has been Associate Editor-in-Chief of IEEE Computer and of the Journal on Software and System Modeling, as well as a member of the editorial boards of the Journal on Software and Systems, and the Journal of Object Technology. He received an engineering degree from Telecom Bretagne in 1986, and a Ph.D. degree in Computer Science from the University of Rennes, France, in 1989.

Title:
The Quest for the GREAL

Abstract:
Efficiently managing variability remains a central challenge in software engineering. While variability modeling has reached maturity, the realization of variability, i.e., bridging feature models with base assets to produce resolved models, continues to pose significant difficulties. In this keynote, we revisit some traditional approaches to variability realization, such as conditional compilation, object-oriented design, aspects, feature toggles and orthogonal variability, and discuss their inherent limitations. Drawing from these insights, we identify composability, openness, flexibility, declarativity, and reusability as the cornerstone principles for effectively managing variability across diverse industrial contexts. We also advocate for a layered approach, enabling progressive adaptation to increasingly complex requirements. Building on this foundation, we introduce preliminary ideas toward the pursuit of GREAL: a Generic REAlization Language. We demonstrate how these concepts have been successfully applied and validated in various industrial settings, offering a starting point for the community to build on.

Sigrid Eldh

Biography:
Sigrid Eldh is an industry veteran. She has a long career in industry-leading software to quality through testing, processes, and organizational development, from startups, government agencies, and consultancy firms, and working at major companies like Ericsson and HP. She got her Masters in the first group of computer scientists at Uppsala University, and she did her PhD at Mälardalen University “On Test Design”, where she still works as a senior lecturer. She is also an Adjunct Professor at Carleton University. She has started several practitioners' clubs like SAST, Swedish Association of Software Testing, and ISTQB, which aims to certify testers. Sigrid Eldh is the Editor-in-Chief for IEEE Software.

Title:
Why Variability is needed in AI & Agentic Automated Software

Abstract:
The largest risk with creating agents is that we solidify processes, inputs, and actions. As we know, there are many ways to solve a problem, create functionality, fix a bug, and optimize a process. Generative AI has an inbuilt variation that instead causes mistrust and serious needs of thorough verification and validation. Through product line variations, and large code sets, one can venture into cloning and duplication, or one can venture into context. Context is “everything,” and in this lies the variability. The mantra of keeping things simple can also be the void of missing opportunities. This leads to serious misjudgment that has consequences down the line. Therefore, we need to infuse variability in our different values, techniques, and approaches to handle the ongoing software evolution.

Keynotes