6 citations · 12 across the 18 of their papers we have counts for
4 papers · 1 filter
Software Performance Engineering for Foundation Model-Powered Software
Haoxiang Zhang, Shi Chang, Arthur Leung +4
The rise of Foundation Models (FMs) like Large Language Models (LLMs) is revolutionizing software development. Despite the impressive prototypes, transforming FMware into productio…
Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmap
Ahmed E. Hassan, Gustavo A. Oliva, Dayi Lin +3
The rise of AI-assisted software engineering (SE 2.0), powered by Foundation Models (FMs) and FM-powered coding assistants, has shown promise in improving developer productivity. H…
Rethinking Software Engineering in the Foundation Model Era: From Task-Driven AI Copilots to Goal-Driven AI Pair Programmers
Ahmed E. Hassan, Gustavo A. Oliva, Dayi Lin +3
The advent of Foundation Models (FMs) and AI-powered copilots has transformed the landscape of software development, offering unprecedented code completion capabilities and enhanci…
Rethinking Software Engineering in the Foundation Model Era: A Curated Catalogue of Challenges in the Development of Trustworthy FMware
Ahmed E. Hassan, Dayi Lin, Gopi Krishnan Rajbahadur +9
Foundation models (FMs), such as Large Language Models (LLMs), have revolutionized software development by enabling new use cases and business models. We refer to software built us…