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The paper reviews the state of search‑based software engineering (SBSE) and its relationship with emerging AI foundation models (FMs) such as large language models. It outlines a research roadmap that examines how FMs can enhance SBSE, how SBSE can advance FMs, and how the two can be integrated. The authors also propose future research directions and opportunities for applying SBSE in new domains enabled by FMs.
By Hassan Sartaj, Shaukat Ali, Paolo Arcaini, Andrea Arcuri
arXiv:2506.03828v4 Announce Type: replace
Abstract: AI for Industrial Asset Lifecycle Management aims to automate complex operational workflows, such as condition monitoring and maintenance schedulin...
By Dhaval Patel, Shuxin Lin, James Rayfield, Nianjun Zhou, Chathurangi Shyalika, Suryanarayana R Yarrabothula, Roman Vaculin, Natalia Martinez, Fearghal O'donncha, Jayant Kalagnanam
arXiv:2602. 14710v2 Announce Type: replace-cross Abstract: Conversational search (CS) requires a complex software engineering pipeline that integrates query reformulation, ranking, and response generation.
By Shaojie Jiang, Svitlana Vakulenko, Maarten de Rijke
arXiv:2603. 03589v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) transform how machine learning (ML) pipelines are developed and evaluated.
By Arnab Phani, Elias Strauss, Sebastian Schelter
Autonomous AI agents can execute complex tasks with limited human review, yet they often lack the grounded operational knowledge to make their outputs not just executable but correct, secure, and maintainable. We introduce SkillCenter, to our knowledge the largest open skill library for agents by total count: 216,938 structured skills across 24 domain bundles.