The notion of continuous software engineering extends practices like continuous integration to view the entire software development lifecycle as a continuous, interconnected flow of activities. At the same time, recent advances in large language models (LLMs) have revolutionized the way machines process natural language—language that plays a central role throughout software engineering, from requirements elicitation and design discussions to documentation.

In this talk, I will outline a vision for the role of models in continuous software engineering, focusing particularly on their use in design activities. I will argue that models will remain central to software engineering, even in an era of AI-assisted development, and explore what future design assistants might look like. One key capability of such assistants will be the ability to establish and use trace links between artifacts. I will present recent results showing how LLMs, combined with heuristic techniques, can achieve high precision and recall in this task.

Looking ahead, I will share our vision for how model-driven techniques can support more agile development of cyber-physical systems, and our ideas how LLMs can contribute to realizing the long-standing goal of model consistency. Finally, time permitting, I will also reflect on the use of LLMs in navigating software engineering literature and research data.

Anne is a professor at Karlsruhe Institute of Technology (KIT), Germany. She received the Diplom degree in informatics from University of Oldenburg, Germany, in 2007 and the PhD degree in informatics from KIT in 2011. After that, she was a Postdoc at the University of Zurich, Switzerland, before joining KIT as an assistant professor in 2013 and becoming a full professor in 2019.

Anne is interested in conciliating model-based software engineering with development processes that have fast and agile feedback cycles and thus combine the benefits of both approaches. In particular, she is interested in tool support for systematic, yet low-cost model-based design space exploration to support making good design decisions. Here, she and her group explore two strands: (1) keeping architectural models consistent with code automatically and (2) using NLP to capture design discussions on e.g. whiteboards and in relating such information to (semi-)formal models and code.

For her work, Anne received the 10-years most influential paper award from ICSA’21, ICPE’21 and ICPE’20 and distinguished reviewer awards from ASE’15, ECSA’22 and ICPE’23.