SSBSE 2025

Best Paper Award

The winners of the SSBSE 2025 best paper award are as follows:

• Didier Ishimwe and Thanhvu Nguyen for LLM-Guided Fuzzing for Pathological Input Generation
• Antony Bartlett, Cynthia Liem and Annibale Panichella for The Pursuit of Diversity: Multi-Objective Testing of Deep Reinforcement Learning Agents

Congratulations for your achievements!

Participant Survey

https://forms.gle/eDEvT29kVLNXaLDk8

SSBSE 2025 Challenge Award

The winner of SSBSE 2025 Challenge award is the authors of “Fuzz Smarter, Not Harder: Towards Greener Fuzzing with GreenAFL”: Ayse Irmak Ercevik, Aidan Dakhama, Melane Navaratnarajah, Yazhuo Cao, Leo Fernandes. The winning team will receive a prize of 700 USD. Congratulation!

Keynote

Prof. Tao Yue (Beihang University, China) delivered the keynote Classical, Quantum, Hybrid, and Beyond: The Changing Landscape of SBSE. Thanks for inspiring talks. This talk was supported by the Software Disaster Research Center funded by the Ministry of Science and ICT through NRF, Republic of Korea.

Welcome message

Welcome to the website of the 17th Symposium on Search-Based Software Engineering 2025 (SSBSE 2025). SSBSE 2025 will take place on November 16th in Seoul, Republic of Korea, co-located with ASE 2025.

Search-based Software Engineering (SBSE) is a research area focused on the formulation of software engineering problems as search problems, and the subsequent use of complex heuristic techniques to attain optimal solutions to such problems. A wealth of engineering challenges – from test generation, to design refactoring, to process organization – can be solved efficiently through the application of automated optimization techniques. SBSE is a growing field – sitting at the crossroads between AI, machine learning, and software engineering – and SBSE techniques have begun to attain human-competitive results.

The Symposium on Search-Based Software Engineering is a venue dedicated to the SBSE research field. We invite the submission of high-quality papers describing novel and original work in all areas of SBSE including, but not limited to, applications of SBSE to novel problems, theoretical analyses of search algorithms for software engineering, rigorous empirical evaluations of SBSE techniques, and reports of industrial experiences.