Generative AI models that generate source code or structured data are becoming important tools in software engineering. However, erroneous or incorrect outputs can cause faults leading to errors in software applications. In this workshop we will discuss these risks and approaches to solve them. In particular, neurosymbolic methods that combine data-driven learning systems and symbolic, logical approaches represent a promising path.

Researchers and practitioners are invited to submit contributions to the following topics (this list is not exhaustive):

  • Generative AI methods in software engineering.
  • Neurosymbolic approaches applied to software engineering problems.
  • Risks of the application of generative AI methods in software engineering.
  • AI-generated computer code.
  • AI-generated structured data (e.g. as instances of domain-specific languages).
  • Generation of error-free source code and/or structure data (including testing).
  • Integration of symbolic approaches in generative models.
  • Uses of symbolic methods for verification/correction of model outputs.
  • AI-supported No-Code or Low-Code approaches.
  • Security in AI-generated code.
  • Industrial applications.
  • AIOps

Important dates

  • Paper submission: October 28 2024 (AoE)
  • Author notifications: November 28 2024 (AoE)
  • Camera-ready version: December 9 2024 (AoE)
  • Workshop: February 24-25 2025

Guidelines

  • Contributions (6-12 pages) will be sent via Easychar using the following link.
  • Contributions can be submitted in German or English language.
  • All contributions shall use the GI LNI-Template (single-column A4 format).
  • All contributions will be peer-reviewed by the program committee. Accepted papers will be published in the conference proceedings (Digital Library der Gesellschaft für Informatik (GI e.V.).

At least one of the authors has to register and attend the workshop to present their contribution (registration deadline: Dec 1 2024).

For all questions/problems please refer to the workshop organizers: Prof.(FH) Dr. Rubén Ruiz Torrubiano