Liebe Besucherinnen und Besucher,
aufgrund unseres Sommerfestes sind wir am 03. September 2026 bis 14 Uhr erreichbar. Am 04. September 2026 sind wir wieder wie gewohnt für Sie da. Vielen Dank für Ihr Verständnis.
Ihr Team von Sack Fachmedien
Wagner / Zhang Search-Based Software Engineering
Erscheinungsjahr 2026
ISBN: 978-3-032-24839-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
17th International Symposium, SSBSE 2025, Seoul, South Korea, November 16, 2025, Proceedings
E-Book, Englisch, 161 Seiten
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-032-24839-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book constitutes the refereed proceedings of the 17th International Symposium on Search-Based Software Engineering, SSBSE 2025, held in Seoul, South Korea, on November 16, 2025.
The 8 full papers, 4 short papers and 2 other papers included in these proceedings were carefully reviewed and selected from 24 submissions. They were organized in the following topical sections: Research Track; RENE/NIER Track; and Challenge Track.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
.- Research Track
.- Constraint-Guided Unit Test Generation for Machine Learning Libraries.
.- KrakQL: LLM-Guided Blind Introspection of GraphQL Schemas.
.- LLM-Guided Fuzzing for Pathological Input Generation.
.- Optimised fitness functions for automated improvement of software’s execution time.
.- Search-based Hyperparameter Tuning for Python Unit Test Generation.
.- Search-based Inference of Class Invariants: How far can Simulated Annealing take us?.
.- The Pursuit of Diversity: Multi-Objective Testing of Deep Reinforcement Learning Agents.
.- RENE/NIER Track.
.- Test Case Generation for Simulink Models: An Experience from the E-Bike Domain.
.- Challenge Track.
.- Fuzz Smarter, Not Harder: Towards Greener Fuzzing with GreenAFL.
.- GA4GC: Greener Agent for Greener Code via Multi-Objective Configuration Optimization.
.- GreenMalloc: Allocator Optimisation for Industrial Workloads.
.- HotCat: Green and Effective Feature Selection for HotFix Bug Taxonomy.




