Much of today’s business runs on software, depends on IT systems and data to perform their daily operations, innovate, and grow. For many companies, the lack of software products that meet their specific needs is a major obstacle to their development.
Software Engineering (SE) as a discipline aims at making software development an efficient, reliable, and predictable engineering process. AI is increasingly part of SEs ever-growing toolbox as both a solution component in the systems developed and to support the development process itself.
Model-based low- or no-code methods based on domain-specific languages have gained popularity in recent years by taking a more business-oriented approach, hiding technical complexity, making software development more productive and less error prone. They are natural companions to AI which is often intrinsically model-based or can work more effectively at model level.
The workshop will bring together a community of solution experts from business and academia with experts in the problem domains to exchange pose questions exchange ideas. Hosted as part of the STAF multiconference, workshop participants will be able to attend STAF events on the same day, including conference and workshop keynotes, to network and develop new collaborations, business and research opportunities across a range of topics represented by the individual events.
Fri 21 JulDisplayed time zone: London change
09:00 - 10:30
|How I lost my faith (in language technology research)? There and back again.|
Andrzej Wąsowski IT University of Copenhagen, Denmark
11:00 - 12:30
|AI and the Evolving Software Engineering Requirements of Industrial Digital Twins|
Frank McQuade Bloc Digital
|How to Speak Hypercar—Lessons Learned From Developing a Model Based Domain Specific Language to Capture Gordon Murray’s Electronic Architecture|
Glynn Beeken Gordon Murray Electronics
13:30 - 15:00
|Using ChatGPT for Software Modelling. Current Status and Future Opportunities|
Antonio Vallecillo University of Málaga, Spain
|Panel Discussion: Challenges and opportunities for AI in Software Engineering|
Call for Papers
The aim of this workshop is to explore and present the challenges and solutions businesses encounter in the application of AI in software engineering. We are especially interested in
- model-based, low- or no-code methods, and domain-specific languages
- software engineer tools for developing or supported by AI solutions
- AI for code generation, debugging, testing, documentation, and error correction
- design and process optimisation and prediction based on AI, e.g., in digital twins
- applications of AI and model-based methods in application domains such as manufacturing, health, transport, energy, etc.
Companies and researchers are invited to submit extended abstracts of up to two pages relevant to the workshop’s topics and their application in industry. Abstracts could describe or suggest solutions or pose open challenges. Selected contributions will be presented at the workshop in plenary and discussion sessions.