Daily Arxiv

This page organizes papers related to artificial intelligence published around the world.
This page is summarized using Google Gemini and is operated on a non-profit basis.
The copyright of the paper belongs to the author and the relevant institution. When sharing, simply cite the source.

Search-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmap

Created by
  • Haebom

Author

Hassan Sartaj, Shaukat Ali, Paolo Arcaini, Andrea Arcuri

Outline

This paper presents a research roadmap for search-based software engineering (SBSE), which integrates metaheuristic search techniques with software engineering. Specifically, it suggests the future evolution of SBSE with the emergence of foundation models (FMs) such as large-scale language models (LLMs), and suggests research directions for advancing SBSE through integration and interaction with FMs. Specifically, it analyzes five key aspects: utilizing FMs in SBSE design, applying FMs to complement SBSEs in SE problem solving, utilizing SBSEs to solve FM problems, adapting SBSE practices to fit SE activities, and exploring synergies between SBSEs and FMs.

Takeaways, Limitations

Takeaways:
SBSE presents the possibility of integrating with FM to contribute to solving various problems in the field of software engineering.
We improve the design and application of SBSE by utilizing FM and suggest new research directions.
Provides research opportunities to address FM challenges and create synergy between SBSE and FM.
Limitations:
This is a paper in the form of a roadmap that presents future research directions, rather than specific research results or experimental data.
No specific technical implementation method or details are presented for the fusion of FM and SBSE.
As this is a new field, verification of actual application and effectiveness is necessary.
👍