Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead

• URL: http://arxiv.org/abs/2506.23762v1
• Date: Mon, 30 Jun 2025 12:09:29 GMT
• Title: Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead
• Authors: Hongzhou Rao, Yanjie Zhao, Xinyi Hou, Shenao Wang, Haoyu Wang,
• Abstract summary: Large language models (LLMs) have redefined artificial intelligence (AI)<n>LLMs development faces increasingly complex challenges throughout its lifecycle.<n>No existing research systematically explores these challenges and solutions from the perspective of software engineering (SE) approaches.
• Score: 4.835306415626808
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid advancement of large language models (LLMs) has redefined artificial intelligence (AI), pushing the boundaries of AI research and enabling unbounded possibilities for both academia and the industry. However, LLM development faces increasingly complex challenges throughout its lifecycle, yet no existing research systematically explores these challenges and solutions from the perspective of software engineering (SE) approaches. To fill the gap, we systematically analyze research status throughout the LLM development lifecycle, divided into six phases: requirements engineering, dataset construction, model development and enhancement, testing and evaluation, deployment and operations, and maintenance and evolution. We then conclude by identifying the key challenges for each phase and presenting potential research directions to address these challenges. In general, we provide valuable insights from an SE perspective to facilitate future advances in LLM development.

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