Advancements in Generative AI and Software Engineering

The field of software engineering is witnessing a significant shift with the integration of Generative AI (GenAI) across various phases of the Software Development Life Cycle (SDLC). This trend is expected to continue, with a focus on advancing AI integration, developing innovative tools, and addressing critical uncertainties in areas such as reliability, accountability, security, and data privacy. Notably, the use of GenAI in software engineering is moving beyond code generation, with an emphasis on collaborative approaches that position AI as a partner rather than a replacement for human expertise.

Some noteworthy papers in this area include: The paper on Generative AI in Automotive highlights the transformative potential of GenAI in the automotive industry, enabling novel applications across vehicle design, manufacturing, and in-vehicle user experience. The paper on Lessons Learned from the Use of Generative AI in Engineering and Quality Assurance of a WEB System for Healthcare provides valuable insights for software organizations seeking to innovate their development practices with GenAI.

Sources

On the Marriage of Theory and Practice in Data-Aware Business Processes via Low-Code

Gen AI in Automotive: Applications, Challenges, and Opportunities with a Case study on In-Vehicle Experience

Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification

Lessons Learned from the Use of Generative AI in Engineering and Quality Assurance of a WEB System for Healthcare

AI for Requirements Engineering: Industry adoption and Practitioner perspectives

The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Project

Lost in Code Generation: Reimagining the Role of Software Models in AI-driven Software Engineering

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