Reflecting on Empirical and Sustainability Aspects of Software Engineering Research in the Era of Large Language Models
Reflecting on Empirical and Sustainability Aspects of Software Engineering Research in the Era of Large Language Models
David Williams,Max Hort,3 Authors,Federica Sarro
TLDR
The results provide a structured overview of current LLM-based SE research at ICSE, highlighting both encouraging practices and persistent shortcomings and recommendations to strengthen benchmarking rigour, improve replicability, and address the financial and environmental costs of LLM-based SE.
Abstract
Software Engineering (SE) research involving the use of Large Language Models (LLMs) has introduced several new challenges related to rigour in benchmarking, contamination, replicability, and sustainability. In this paper, we invite the research community to reflect on how these challenges are addressed in SE. Our results provide a structured overview of current LLM-based SE research at ICSE, highlighting both encouraging practices and persistent shortcomings. We conclude with recommendations to strengthen benchmarking rigour, improve replicability, and address the financial and environmental costs of LLM-based SE.