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 Towards Sustainable AI-Supported Software Development:
Balancing Efficiency and Developer Needs |  | SUN Zhensu PhD Candidate
School of Computing and Information Systems
Singapore Management University
| Research Area Dissertation Committee Research Advisor Committee Members |
| | Date 2 February 2026 (Monday) | Time 10:00am - 11:00am | Venue Meeting room 4.4, Level 4
School of Computing and Information Systems 1,
Singapore Management University,
80 Stamford Road
Singapore 178902 | Please register by 29 January 2026. We look forward to seeing you at this research seminar. 
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| | ABOUT THE TALK The rapid integration of Large Language Models (LLMs) into software development has catalyzed a paradigm shift from human-only development to a collaborative human-AI software ecosystem. While this transition offers significant short-term performance gains, the long-term viability of AI-supported development is increasingly challenged by escalating computational costs, the accumulation of technical debt, and the erosion of human oversight. This dissertation proposal argues that sustainability must be a foundational requirement, not an afterthought, for the future of AI-supported software development.
To facilitate this vision, this dissertation proposal presents seven research contributions, covering three interdependent pillars: Environmental Sustainability, Economic Sustainability, and Social Sustainability. For environmental sustainability, this dissertation proposal presents a line of work on AI-friendly code representation to minimize the computational footprint during software development. For Economic Sustainability, I propose to boost real developer productivity through preventing productivity loss from unhelpful suggestions and increasing developer intent fulfilment during AI-supported software development. For Social Sustainability, this proposal identifies new attach channel and explores the risks of autonomous AI behaviour. | | | SPEAKER BIOGRAPHY Zhensu SUN is a PhD candidate at Singapore Management University, under the supervision of Prof. David LO. His research focuses on Intelligent Software Engineering. His work has been published on top-tier venues such as ICSE, FSE, ASE, WWW, ISSTA, and TOSEM. He received the ACM SIGSOFT Distinguished Paper Award at ISSTA'24 and was nominated at ICSE'22. He is also a winner of 2024 ByteDance Scholarship. |
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